Dr. Maxime Labonne.
J. P. Morgan
28th February 2024, 04:00pm – 05:00pm (GST)
| Title: | Introduction to model merging |
| Abstract: | Model merging is a technique that combines two or more LLMs into a single model. It’s a relatively new and experimental method to create new models for cheap (no GPU required). It works surprisingly well and produced many state-of-the-art models on the Open LLM Leaderboard. In this talk, we will introduce the main merge techniques and provide tips and tricks to improve your merges. |
| Bio: | Maxime Labonne is a seasoned Machine Learning Scientist and a thought leader in the LLM community. He is currently working at J.P. Morgan in London and holds a Ph.D. in Machine Learning from the Polytechnic Institute of Paris. An active blogger, he has made numerous contributions to the open-source community, including the LLM Course on GitHub, automated tools such as LLM AutoEval, and many state-of-the-art models and architectures like Phixtral and NeuralBeagle. He is the author of the best-selling book "Hands-On Graph Neural Networks using Python," published by Packt. Connect with him on LinkedIn and Twitter @maximelabonne. |