Llama 2 is a state-of-the-art language model developed by Meta that offers enhancements in terms of scale, efficiency, and performance. It is the successor to the original LLaMA model and has been trained using publicly available online data to learn general language patterns and acquire a broad understanding of language structure. The model incorporates several innovative elements, including RMSNorm pre-normalization, SwiGLU activation, and Rotary embeddings, which contribute to its ability to maintain context over longer stretches of conversation and offer more precise attention to relevant details in dialogue. Llama 2 has been trained with a reinforcement learning approach to produce non-toxic and family-friendly output, and it has been fine-tuned through supervised learning and reinforcement learning with human feedback. The model is open-source and available for download under a community license, making it an economical option for businesses that want to integrate the model with their internal data and fine-tune it for specific use cases while preserving privacy. Llama 2's flexibility, versatility, safety, and customization capabilities make it a valuable asset across sectors, including chatbot applications, summarization, translation, content generation, and coding assistance. The model is designed to be as safe or safer than other models in the market and offers an alternative for those seeking to develop on a platform that supports modification and redistribution.