pinned
Running
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29
Decoding Visualizer
✍
View how beam search decoding works, in detail!
Agents Course on Hugging Face Learn
\nThis interactive, certified course will guide you through building and deploying your own AI Agents.
\n📝 Register here for the course
\n📖 Check out the course material here
\n\n\nCourse Syllabus
\nHere is the general syllabus for the course. With each unit a more detailed list of topics will be released.
\n\n\t\n\t\t
\n
\n| Chapter | \nTopic | \nDescription | \n
|---|---|---|
| 0 | \nOnboarding | \nSet you up with the tools and platforms that you will use. | \n
| 1 | \nAgent Fundamentals | \nExplain Tools, Thoughts, Actions, Observations, and their formats. Explain LLMs, messages, special tokens and chat-template. Show a simple use case in generic python functions. | \n
| 2 | \nFrameworks | \nUnderstand how the fundamentals are implemented in popular libraries : smolagents, LangGraph, LLamaIndex | \n
| 3 | \nUse Cases | \nLet’s build some real life use cases ( open to PRs 🤗 from experienced Agent builders ) | \n
| 4 | \nFinal Assignment | \nBuild an agent for a selected benchmark (GAIA) | \n
Units contain: live session, written material, and interactive quiz.
\nPrerequisites
\n- \n
- Python programming \n
- LLM prompting \n
- A Hugging Face account ( free ) : Register here \n
Community
\nIf you would like to study, contribute to, or discuss the agents course then join the Hugging Face Discord.
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