Unlocking the Potential of Multimodality with Pali-Gemma. In this session, I’ll dive into the concepts and applications of multimodality, showcasing how combining multiple forms of data can enhance AI model capabilities. I’ll walk through the process of training on Colab/Kaggle, highlighting each step from data preparation to fine-tuning. Following the training phase, I’ll demonstrate how we can leverage Hugging Face Spaces for inference and deployment, providing a practical approach to deploying powerful Vision-Language Models (VLMs) in real-world applications. This session will serve as a comprehensive guide for anyone interested in building and deploying multimodal AI solutions, showing how PaLI-Gemma, a state-of-the-art model, is trained and implemented. By the end, participants will have a solid understanding of how multimodal RAGs work and how to bring them to production efficiently.