What is LLM fine-tuning?

What this post added

This post provides a comprehensive overview of LLM fine-tuning, explaining its benefits (cost, performance, customization) and common use cases. It details the steps involved, from choosing a base model and preparing datasets (including prompt engineering and special tokens) to the training process itself. The post highlights Modal as a configurable platform for running fine-tuning code, emphasizing its ability to provide on-demand GPUs and simplify infrastructure management. It also mentions Modal's existing tutorial for LLM fine-tuning.