Large Language Models and Foundation Models for Materials Science
Abstract
The emergence of open-source foundation models in materials science is revolutionizing how researchers approach molecule design, property prediction, and materials discovery. This hands-on tutorial is designed to introduce participants to these powerful tools, focusing on SMILES, SELFIES, and molecular graph-based models. Participants will gain practical experience in fine-tuning these models with custom datasets, visualizing molecular embeddings, and executing downstream tasks such as property prediction and molecule generation. Through interactive sessions, attendees will learn how to leverage these models to accelerate their research and development processes. The tutorial will walk participants through the entire workflow, from data preprocessing and model customization to evaluating results and interpreting insights.