Maxime Labonne

In this podcast, Maxime Labonne discusses building 7B params LLMs, steps to create LLMs, RAG vs fine-tuning, DPO vs RLHF, and deploying LLMs in production. He shares insights on merging models for enhanced performance, getting into GenAI, and using ChatGPT for various applications. From cybersecurity to AI, Maxime's journey and career advice offer valuable perspectives on entering the field of AI.

In this episode, Maxime Labonne, Senior Machine Learning Scientist at JPMorgan and author of Hands on GNNs book, talks about the increasingly popular technique of model merging and its impact on the AI community. He discusses the creation of LazyMergeKit, a wrapper on top of MergeKit by Charles Goddard, which has become a widely used library for model merging. The episode also covers the challenges of running benchmarks and creating leaderboards, the use of LNMA FITU for evaluations, and Maxim's involvement in training small language models for playing chess.