Meta Llama

Meta Llama is an open-source large language model that's designed to make AI accessible and responsible for developers, researchers and businesses. The project includes a collection of models and supporting resources to be used in a variety of tasks, including programming, translation, dialogue generation and more.

Some of the key aspects of Meta Llama include:

• Meta Llama 3: An open-source language model that can be used for a variety of tasks, available in two sizes, 8B and 70B.
• Meta Code Llama: A model tuned for code generation and natural language about code, available in three sizes, 7B, 13B and 70B.
• Meta Llama Guard: A collection of open trust and safety tools and evaluations.

Meta Llama is designed for both research and commercial use, with licenses that make it broadly available. The models are designed to be powerful and flexible, so they can be used in a variety of settings. The Code Llama models, for example, are fine-tuned for the Python programming language and can generate code with up to 100,000 tokens of context.

Developers can get access to the Meta Llama models through a variety of channels, including GitHub repositories and hosting services like Microsoft, Amazon Web Services and Hugging Face. The project also includes a Responsible Use Guide that developers can use to build and deploy their own products, covering issues like content policies, data preparation and safety assessments.

The Meta Llama project is designed to be community focused, with an invitation to participate and provide feedback. That includes a wide range of allies from the tech industry, academia and policy circles. The open approach is designed to make AI tools more accessible and to encourage innovation while promoting safety and responsible development practices.

For developers who want to try out large language models, Meta Llama is a good starting point. The project's responsibility focus and open collaboration approach make it a good option for those who want to build and deploy AI-powered products.

Published on June 13, 2024