Refining Large Language Models: Fine-Tuning Strategies and Practices

This technical report, "The Ultimate Guide to Fine-Tuning LLMs," offers a comprehensive review of techniques for adapting large language models. It traces the evolution of LLMs , distinguishes between various fine-tuning methodologies , and outlines a seven-stage pipeline for the process. The report also examines critical aspects like data preparation, training setup, evaluation, deployment, and ongoing maintenance . Furthermore, it addresses emerging challenges and research directions , including multimodal LLMs, scalability, ethical considerations, and integration with other technologies, aiming to be a valuable resource for both researchers and practitioners. https://arxiv.org/pdf/2408.13296