RAFT – A Fine-Tuning and RAG Approach to Domain-Specific Question Answering

As the applications of large language models expand into specialized domains, the need for efficient and effective adaptation techniques becomes increasingly crucial. Enter RAFT (Retrieval Augmented Fine Tuning), a novel approach that combines the strengths of retrieval-augmented generation (RAG) and fine-tuning, tailored specifically for domain-specific question answering tasks. The Challenge of Domain Adaptation While LLMs […]

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applications artificial intelligence domain domains expand fine-tuning gpt-3.5 language language models large language large language models llm novel question question answering raft rag retrieval retrieval-augmented retrieval augmented generation supervised fine-tuning tasks