831: PyTorch Lightning, Lit-Serve and Lightning Studios, with Dr. Luca Antiga
Super Data Science: ML & AI Podcast with Jon Krohn
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Optimizing Language Model Training
This chapter explores the challenges of training large language models, particularly the heavy GPU infrastructure required. It introduces the Thunder compiler as a solution for optimization and discusses the balance between small and large language models, emphasizing the operational efficiencies and evolving capabilities of smaller models. The conversation also addresses in-context learning, model size implications, and the future of model performance enhancements.
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