LLM Course

0. Setup

1. Transformer models

2. Using 🤗 Transformers

3. Fine-tuning a pretrained model

4. Sharing models and tokenizers

The Hugging Face Hub Using pretrained models Sharing pretrained models Building a model card Part 1 completed!End-of-chapter quiz

5. The 🤗 Datasets library

6. The 🤗 Tokenizers library

7. Classical NLP tasks

8. How to ask for help

9. Building and sharing demos

10. Curate high-quality datasets

11. Fine-tune Large Language Models

12. Build Reasoning Models new

Course Events

Join the Hugging Face community

and get access to the augmented documentation experience

Collaborate on models, datasets and Spaces

Faster examples with accelerated inference

Switch between documentation themes

to get started

Part 1 completed!

This is the end of the first part of the course! Part 2 will be released on November 15th with a big community event, see more information here.

You should now be able to fine-tune a pretrained model on a text classification problem (single or pairs of sentences) and upload the result to the Model Hub. To make sure you mastered this first section, you should do exactly that on a problem that interests you (and not necessarily in English if you speak another language)! You can find help in the Hugging Face forums and share your project in this topic once you’re finished.

We can’t wait to see what you will build with this!

Update on GitHub

←Building a model card End-of-chapter quiz→