LLaMA 2 Chat

LLaMA 2 Chat is trained with supervised instruction data and preference optimization so it responds in a cooperative, safety aware style. It keeps context across turns, explains steps when asked, and formats outputs predictably for apps that need JSON or code blocks. Models ship in several sizes, which makes it easy to trade accuracy for speed and run locally with quantization or in the cloud for higher throughput. Teams use it as a base for self hosted assistants, retrieval augmented systems, and domain fine tunes, since weights and tooling are widely available and easy to adapt. Compared with base LLaMA 2, the chat version is more steerable and aligned, which reduces prompt engineering and improves reliability in production style workflows.