How He Built The Best 7B Params LLM with Maxime Labonne #43
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Enhancing Language Models with RAG and Fine-Tuning
The chapter discusses the benefits of using Retriever-Augmented Generation (RAG) in conjunction with supervised fine-tuning to improve language models by incorporating external context. The conversation highlights the importance of relevant datasets, outlines the RAG process of retrieving information without training data, and emphasizes the need for ensuring appropriate model behaviors through concepts like LLM chef and DPO.
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