Retrieval-Augmented Generation (RAG) and fine-tuning are two sophisticated approaches that significantly enhance the capabilities of language models. Both strategies have distinct methodologies and applications, yet they share a common goal: improving the model‘s performance by leveraging data in innovative ways.
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