How to Fine-Tune an LLM: An End-to-End Guide

I ended up fine tuning a mistral 7b to outperform our costly foundational model and saved $300k. I previously thought that fine tuning was pointless (it's definitely not) and that all these problems could be solved with RAG (they can't).

The truth is, a LoRA/QLoRA adapter is extremely useful for many cases, and can dramatically outperform RAG with aggressive system prompts.

With this guide, I want to help people understand the reasonableness of QLoRA on a consumer grade GPU (you might even be able to fine-tune on a colab t4).

It also includes a deep dive on the mathematics behind LoRA/QLoRA as well.

Let me know if I can help you out with your fine tuning pipeline. It certainly works!