This repository provides a comprehensive guide and practical recipes for building applications with Meta's Llama family of large language models. It targets developers and researchers looking to implement inference, fine-tuning, and end-to-end use cases, offering community-driven approaches and the latest techniques for text and vision models.

How It Works

The cookbook offers a structured approach to leveraging Llama models, categorized into "Getting Started" recipes for inference, fine-tuning, and Retrieval-Augmented Generation (RAG), and "End-to-End Use Cases" demonstrating practical applications across various domains. It also includes integrations with third-party providers and showcases advanced techniques like handling long contexts and custom data analysis.

Quick Start & Requirements

• Installation typically involves cloning the repository and following specific recipe instructions, often requiring Python environments.
• Prerequisites vary by recipe but commonly include Python, PyTorch, and potentially specific libraries for data handling or model integration.
• Access to Llama model weights is required, which may involve an application process.
• Refer to individual recipe directories for detailed setup and dependencies.

Highlighted Details

• Features recipes for the latest Llama 4 models, including long context handling and custom analysis.
• Demonstrates integration with external services like WhatsApp.
• Covers foundational tasks such as inference, fine-tuning, and RAG.
• Includes a refactored llama-recipes library with fine-tuning FAQs.

Maintenance & Community

• The project is actively maintained by Meta.
• Contribution guidelines are available in CONTRIBUTING.md.
• Links to official Llama models and Acceptable Use Policies are provided for various Llama versions.

Licensing & Compatibility

• The repository itself is likely under a permissive license, but usage of Llama models is governed by Meta's specific Llama licenses and Acceptable Use Policies for each version (Llama 4, 3, 2).
• Commercial use and closed-source linking are subject to the terms of the respective Llama model licenses.

Limitations & Caveats

• The repository underwent a recent refactor, and older links or folders might be found in the archive-main branch.
• Specific model weights are required and may have usage restrictions based on Meta's licensing.