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4min chapter
801: Merged LLMs Are Smaller And More Capable, with Arcee AI's Mark McQuade and Charles Goddard
Super Data Science: ML & AI Podcast with Jon Krohn
Benefits of Model Merging and Case Studies on Smaller Merged Models
Exploring the benefits of model merging in machine learning, such as preventing catastrophic forgetting and improving model capabilities, alongside discussing the advantages of smaller merged models over closed source models. The chapter also covers a machine learning foundations curriculum and a case study on fine-tuning open source models for particular tasks.
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