Agents Course documentation

Conclusion

Agents Course

Unit 0. Welcome to the course

Live 1. How the course works and Q&A

Unit 1. Introduction to Agents

Unit 2. Frameworks for AI Agents

Unit 2.1 The smolagents framework

Unit 2.2 The LlamaIndex framework

Unit 2.3 The LangGraph framework

Unit 3. Use Case for Agentic RAG

Unit 4. Final Project - Create, Test, and Certify Your Agent

Bonus Unit 1. Fine-tuning an LLM for Function-calling

Introduction What is Function Calling? Let's Fine-Tune your model for Function-calling Conclusion

Bonus Unit 2. Agent Observability and Evaluation

Bonus Unit 3. Agents in Games with Pokemon

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

Conclusion

Congratulations on finishing this first Bonus Unit 🥳

You’ve just mastered understanding function-calling and how to fine-tune your model to do function-calling!

If we have one piece of advice now, it’s to try to fine-tune different models. The best way to learn is by trying.

In the next Unit, you’re going to learn how to use state-of-the-art frameworks such as smolagents, LlamaIndex and LangGraph.

Finally, we would love to hear what you think of the course and how we can improve it. If you have some feedback then, please 👉 fill this form

Keep Learning, Stay Awesome 🤗

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