Fine-Tuning LLMs With Retrieval Augmented Generation (RAG)

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This approach is a novel implementation of RAG called RA-DIT (Retrieval Augmented Dual Instruction Tuning) where the RAG dataset (query, context retrieved and response) is used to to fine-tune a LLM…

Fine-Tuning LLMs With Retrieval Augmented Generation (RAG), by Cobus Greyling

Retrieval Augmented Generation - A Simple Introduction

Bruno Vicente posted on LinkedIn

Scale AI on X: Retrieval Augmented Generation (RAG) vs Fine-tuning is a false dichotomy. These two techniques are complementary not in competition. In fact, they're often needed together. For example, a tax

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Retrieval augmented generation: Keeping LLMs relevant and current - Stack Overflow

Giovanni Lima on LinkedIn: Fine-Tuning LLMs With Retrieval Augmented Generation (RAG)

Fine Tuning or Retrieval Augmented Generation (RAG), That Is the Question, by Peng Liu, Mar, 2024

NEFTune”: Discover How Noisy Embeddings Act as Catalyst to Improve Instruction Finetuning!, by AI TutorMaster

Cobus Greyling on LinkedIn: Fine-Tuning LLMs With Retrieval Augmented Generation (RAG)

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Understanding RAG and fine-tuning of LLMs, by Ashok Poudel

List: Chatbot, Curated by Anuj Mp