Dear learner,

Today we’re introducing a new short course made in collaboration with Hugging Face: Open Source Models with Hugging Face.

In this course, you’ll learn how to find and filter open source models on Hugging Face Hub to perform text, audio, image, and multimodal tasks using the Hugging Face transformers library. You’ll also learn to easily share your AI apps with a user-friendly interface or via API and run them locally and on the cloud using Gradio and Hugging Face Spaces.

What you'll do in this course:

• Use the transformers library to turn a small language model into a chatbot capable of multi-turn conversations to answer follow-up questions.
• Translate between languages, summarize documents, and measure the similarity between two pieces of text, which can be used for search and retrieval.
• Convert audio to text with Automatic Speech Recognition (ASR), and convert text to audio using Text to Speech (TTS).
• Perform zero-shot audio classification, to classify audio without fine-tuning the model.
• Generate an audio narration describing an image by combining object detection and text-to-speech models.
• Identify objects or regions in an image by prompting a zero-shot image segmentation model with points to identify the object that you want to select.

The course will provide you with the building blocks that you can combine into a pipeline to build your AI-enabled applications!

Learn how to easily build AI applications using open source models and Hugging Face tools.

• Find and filter open source models on Hugging Face Hub based on task, rankings, and memory requirements.
• Write just a few lines of code using the transformers library to perform text, audio, image, and multimodal tasks.
• Easily share your AI apps with a user-friendly interface or via API and run them on the cloud using Gradio and Hugging Face Spaces.

Beginner Maria Khalusova, Marc Sun, Younes Belkada Prerequisite recommendation: This is a beginner-friendly course.