Multimodal Model Training
Luke discusses the dual-step training pipeline for large language models, emphasizing the importance of both pre-training and fine-tuning. He highlights the adaptation of this process for multimodal models, where tasks can involve both text and images, allowing for enhanced generalization and control. By leveraging a tokenization approach, the model can effectively integrate various data types, making it a versatile tool in the AI landscape.In this clip
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The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Scaling Multi-Modal Generative AI with Luke Zettlemoyer - 650
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