Fine-Tuning

In one sentenceTraining an existing model further on your own examples so it gets better at a specific task or style.

What it means

Fine-tuning adjusts a model's internal Parameters using hundreds or thousands of examples of the output you want. It is more permanent than prompting, and more work.

For most businesses, good prompts, Few-Shot Prompting examples and RAG get you most of the way without fine-tuning.

How to use it

• Try prompting and examples first. Consider fine-tuning only when you have lots of high-quality examples and need consistent output at scale.

Related terms

Few-Shot Prompting RAG Training Data Foundation Model