meta-llama/llama-cookbook

Health v2 · maintenance only

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18559 stars · 2756 forks observed · 2026-09-21

What it is AI-extracted, prompt v1, taxonomy v1, 2026-10-19, confidence 0.97

The Llama Cookbook is a collection of Jupyter notebooks and scripts that demonstrate how to use Meta's Llama models for inference, fine‑tuning, and retrieval‑augmented generation. It provides end‑to‑end recipes, integrations with LangChain, and guidance for various provider services.

Use cases

• run inference with Llama 4 models via the Meta Model API
• fine‑tune a Llama model on a custom dataset for domain adaptation
• build a RAG pipeline that queries external data using Llama embeddings
• create a multimodal chatbot that handles text and images with Llama
• integrate Llama models into LangChain workflows for tool use and agentic patterns

When to choose

• you need quick, runnable examples to get started with Llama models
• you want step‑by‑step notebooks for fine‑tuning, inference, or RAG
• you are exploring integrations with LangChain or other agent frameworks
• you prefer Python/Jupyter environments for prototyping

When to avoid

• you require a production‑grade SDK or library with strict versioning guarantees
• you need a lightweight pure‑Python package without heavy notebook dependencies
• your project is not based on Python or Jupyter notebooks

Facets

library · maturity active

llm-inference llm-training rag api-framework artificial-intelligence machine-learning large-language-models chatbots python windows cloud notebooks meta-llama tutorial example-recipes langchain-integration retrieval-augmented-generation jupyter-notebook linux macos

Member repositories

For agents

markdown · JSON · MCP: product_card(name="metainternal/llama-cookbook")