Llama 2: Open Foundation and Fine-Tuned Chat Models

Deep Papers is a podcast series featuring deep dives on today’s seminal AI papers and research. Each episode profiles the people and techniques behind cutting-edge breakthroughs in machine learning. This episode is led by Aparna Dhinakaran ( Chief Product Officer, Arize AI) and Michael Schiff (Chief Technology Officer, Arize AI), as they discuss the paper "Llama 2: Open Foundation and Fine-Tuned Chat Models."In this paper reading, we explore the paper “Developing Llama 2: Pretrained Large Language Models Optimized for Dialogue.” The paper introduces Llama 2, a collection of pretrained and fine-tuned large language models ranging from 7 billion to 70 billion parameters. Their fine-tuned model, Llama 2-Chat, is specifically designed for dialogue use cases and showcases superior performance on various benchmarks. Through human evaluations for helpfulness and safety, Llama 2-Chat emerges as a promising alternative to closed-source models. Discover the approach to fine-tuning and safety improvements, allowing us to foster responsible development and contribute to this rapidly evolving field.Full transcript and more here: https://arize.com/blog/llama-2-open-foundation-and-fine-tuned-chat-models-paper-reading/Follow AI__Pub on Twitter. To learn more about ML observability,  join the Arize AI Slack community or get the latest on our LinkedIn and Twitter.Learn more about AI observability and evaluation, join the Arize AI Slack community or get the latest on LinkedIn and X.