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TheHuggingFaceAgentsCourse

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  • 最終更新: 2025/07/04
  • 読み取り時間: 02:38

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Content

The course is divided into 4 units. These will take you from the basics of agents to a final assignment with a benchmark.

Sign up here (it’s free) 👉 https://bit.ly/hf-learn-agents

You can access the course here 👉 https://hf.co/learn/agents-course

Unit Topic Description

0

Welcome to the Course

Welcome, guidelines, necessary tools, and course overview.

1

Introduction to Agents

Definition of agents, LLMs, model family tree, and special tokens.

1 Bonus

Fine-tuning an LLM for Function-calling

Learn how to fine-tune an LLM for Function-Calling

2

Frameworks for AI Agents

Overview of smolagents, LangGraph and LlamaIndex.

2.1

The Smolagents Framework

Learn how to build effective agents using the smolagents library, a lightweight framework for creating capable AI agents.

2.2

The LlamaIndex Framework

Learn how to build LLM-powered agents over your data using indexes and workflows using the LlamaIndex toolkit.

2.3

The LangGraph Framework

Learn how to build production-ready applications using the LangGraph framework giving you control tools over the flow of your agent.

2 Bonus

Observability and Evaluation

Learn how to trace and evaluate your agents.

3

Use Case for Agentic RAG

Learn how to use Agentic RAG to help agents respond to different use cases using various frameworks.

4

Final Project - Create, Test and Certify Your Agent

Automated evaluation of agents and leaderboard with student results.

3 Bonus

Agents in Games with Pokemon

Explore the exciting intersection of AI Agents and games.

Prerequisites

  • Basic knowledge of Python

  • Basic knowledge of LLMs

Contribution Guidelines

If you want to contribute to this course, you’re welcome to do so. Feel free to open an issue or join the discussion in the Discord. For specific contributions, here are some guidelines:

Small typo and grammar fixes

If you find a small typo or grammar mistake, please fix it yourself and submit a pull request. This is very helpful for students.

New unit

If you want to add a new unit, please create an issue in the repository, describe the unit, and why it should be added. We will discuss it and if it’s a good addition, we can collaborate on it.

Citing the project

To cite this repository in publications:

@misc{agents-course,
  author = {Burtenshaw, Ben and Thomas, Joffrey and Simonini, Thomas and Paniego, Sergio},
  title = {The Hugging Face Agents Course},
  year = {2025},
  howpublished = {\url{https://github.com/huggingface/agents-course}},
  note = {GitHub repository},
}
著者:
Hugging Face

The AI community building the future.

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