huggingface/cookbook resource

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2711 stars · 414 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A community-driven collection of Jupyter notebooks from Hugging Face demonstrating practical AI application building with open-source tools and models. It covers tasks like fine-tuning, RAG, agents, and inference, published as part of Hugging Face's learn documentation.

Use cases

• learn how to fine-tune LLMs with TRL and GRPO
• build a RAG pipeline with open-source models
• create AI agents with Hugging Face tools
• find practical notebook examples for machine learning tasks
• post-train a vision-language model for reasoning
• fine-tune LLMs for function calling
• optimize language models with DSPy

When to choose

• you want hands-on, executable notebook examples using open-source models
• you are learning Hugging Face ecosystem tools like Transformers, TRL, and PEFT
• you need practical recipes for LLM fine-tuning, agents, or RAG
• you prefer community-driven, permissively licensed educational content

When to avoid

• you need production-ready software or a maintained library rather than tutorials
• you want a structured course with assessments instead of standalone notebooks
• you need vendor-neutral content independent of the Hugging Face ecosystem

Facets

learning-resource · maturity active

machine-learning llm-inference llm-training rag agent-framework developer-tools machine-learning large-language-models artificial-intelligence tutorials deep-learning python cross-platform jupyter-notebooks cookbook hugging-face open-source-models examples fine-tuning ai-agents

Member repositories

For agents

markdown · JSON · MCP: product_card(name="huggingface/cookbook")