Meta recently launched Llama 2, the next generation of its open source language model, which is available for free for both research and commercial applications. This new version offers significant improvements over its predecessor, Llama 1, including double the context length, training on 2 trillion tokens and fine-tuned models on over 1 million human annotations.
Llama 2 outperforms other open-source language models in many external benchmarks, including reasoning, coding, proficiency and knowledge tests. The model has been pre-trained on publicly available online data sources, and the fine-tuned model, Llama Chat, uses publicly available instruction datasets and over 1 million human annotations. There is also Code Llama, a code generation model trained on 500 billion tokens of code and supporting common programming languages such as Python, C++, Java, PHP, Typescript, C# and Bash.
Meta recognizes its responsibility and has established a series of resources for all users of Llama 2, including individuals, developers, researchers, academics, and companies of all sizes. The Responsible Use Guide provides developers with best practices and considerations for developing products powered by large language models in a responsible manner.
Meta has also partnered with Microsoft to promote Llama 2, but the model is not exclusive and is also available to users of Amazon Web Services, Hugging Face and other platforms.
Llama 2 is available in three variants, with 7 billion, 13 billion and 70 billion parameters respectively. A notable feature of Llama 2 is the integration of Grouped Query Attention (GQA), a new mechanism that combines the speed of inaccurate Multi Query Attention with the accuracy of Multi Head Attention. This is particularly useful for very large language models, as it makes training more complex but significantly increases inference speed.
An important aspect of Llama 2 is that it is open source, which gives startups and companies the opportunity to use the cutting-edge AI as a basis and develop customized offerings based on it. This open innovation strategy allows the community to quickly identify and solve problems, improve the tools and fix vulnerabilities.
Llama 2 represents a significant advance in the development of open source language models. With improvements in model size, context length and fine-tuning to human annotations, Llama 2 provides a powerful and flexible solution for researchers and companies who want to be at the forefront of AI development. The fact that it is open source encourages collaboration and innovation across the AI community.
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