LLM Course documentation
Argilla, check!
0. Setup
1. Transformer models
2. Using 🤗 Transformers
3. Fine-tuning a pretrained model
4. Sharing models and tokenizers
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
Introduction to ArgillaSet up your Argilla instanceLoad your dataset to ArgillaAnnotate your datasetUse your annotated datasetArgilla, check!End-of-chapter quiz
11. Fine-tune Large Language Models
12. Build Reasoning Models new
Course Events
Argilla, check!
That’s all! Congrats! 👏
In this chapter, you learnt the basic steps to:
- set up Argilla.
- annotate to improve the quality of your dataset.
- adapt an existing dataset and re-use it for a different NLP task.
- share your annotated dataset with the community in the Hugging Face Hub.
What’s next?
- Check more step-by-step tutorials for other popular tasks in the tutorials page.
- You can also explore other examples of datasets in this demo.
- If you’d like to keep learning about Argilla and more advanced features, check the Argilla documentation.