How to Finetune LLMs: From Training Data to Deployment

TL;DR Fine-tuning adapts a pretrained LLM to a specific task using examples of the responses you want. It can improve output consistency and instruction following, though training takes time. Start with prompt tests and representative evaluations to decide whether to change the model’s weights.