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

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 an LLM vs. RAG: What's Best for Your Corporate Chatbot?

Types of RAG: An Overview. Retrieval Augmented Generation is the…, by Jayanth Krishnaprakash

RAGs from scratch — Why & What?!!, by Arion Das, Feb, 2024

Fine-Tuning or RAG?. Comparing different LLM knowledge…

A Brief Introduction to Retrieval Augmented Generation(RAG), by Florian June

Retrieval Augmented Generation (RAG) Safeguards Against LLM Hallucination

Large Language Model (LLM) Stack — Version 5

RAG Vs Fine-Tuning Vs Both: A Guide For Optimizing LLM Performance - Galileo

Retrieval-Augmented Generation (RAG) vs LLM Fine-Tuning

Fine-tuning with Cohere: Part 4 — Unlocking the Power of Custom

Fine-tuning an LLM vs. RAG: What's Best for Your Corporate Chatbot?

RAG Vs Fine-Tuning Vs Both: A Guide For Optimizing LLM Performance - Galileo

Fine-tuning large language models (LLMs) in 2024

Fine-Tuning Transformers for NLP

What is supervised fine-tuning? — Klu

Fine-Tuning Large Language Models for Decision Support: A Comprehensive Guide, by Anthony Alcaraz

Fine-Tuning LLaMA 2: A Step-by-Step Guide to Customizing the Large Language Model