LLaMA2

LLaMA 2, short for Large Language Model Meta AI 2, is a family of transformer-based language models developed by Meta AI as the successor to the original LLaMA. The model family includes several sizes, notably 7 billion, 13 billion, and 70 billion parameters, enabling a range of deployment options on commodity hardware. In addition to the base models, Meta released chat-optimized variants under the name Llama 2-Chat, designed for instruction-following and dialogue.

LLaMA 2 models are trained on a mixture of publicly available data and licensed data, with safety mitigations and alignment tuning incorporated into the development process. They are intended for a broad set of natural language tasks, including text generation, summarization, translation, and question answering. The models are released with a permissive licensing framework intended to facilitate research and commercial use under the Community License Agreement, subject to specified terms and attribution.

The release strategy emphasizes accessibility and interoperability, providing public weights and documentation to support academic and industry experimentation. Since its introduction, LLaMA 2 has been used as a base model for fine-tuning, evaluation, and building conversational AI applications, contributing to the ecosystem of open-weight language models and informing comparisons with other large language models.