diff --git a/docs/source/index.md b/docs/source/index.md
index a6806900cb3c..fbd20a1f9269 100644
--- a/docs/source/index.md
+++ b/docs/source/index.md
@@ -100,6 +100,14 @@ features/compatibility_matrix
 
 % Details about running vLLM
 
+:::{toctree}
+:caption: Training
+:maxdepth: 1
+
+training/trl.md
+
+:::
+
 :::{toctree}
 :caption: Inference and Serving
 :maxdepth: 1
diff --git a/docs/source/training/trl.md b/docs/source/training/trl.md
new file mode 100644
index 000000000000..ebdf593dbde5
--- /dev/null
+++ b/docs/source/training/trl.md
@@ -0,0 +1,13 @@
+# Transformers Reinforcement Learning
+
+Transformers Reinforcement Learning (TRL) is a full stack library that provides a set of tools to train transformer language models with methods like Supervised Fine-Tuning (SFT), Group Relative Policy Optimization (GRPO), Direct Preference Optimization (DPO), Reward Modeling, and more. The library is integrated with 🤗 transformers.
+
+Online methods such as GRPO or Online DPO require the model to generate completions. vLLM can be used to generate these completions!
+
+See the guide [vLLM for fast generation in online methods](https://huggingface.co/docs/trl/main/en/speeding_up_training#vllm-for-fast-generation-in-online-methods) in the TRL documentation for more information.
+
+:::{seealso}
+For more information on the `use_vllm` flag you can provide to the configs of these online methods, see:
+- [`trl.GRPOConfig.use_vllm`](https://huggingface.co/docs/trl/main/en/grpo_trainer#trl.GRPOConfig.use_vllm)
+- [`trl.OnlineDPOConfig.use_vllm`](https://huggingface.co/docs/trl/main/en/online_dpo_trainer#trl.OnlineDPOConfig.use_vllm)
+:::