---
title: "Fine-tuning"
type: "glossary-term"
category: "AI & LLMs"
canonical_url: "https://www.graphcanon.com/glossary/ai-and-llms/fine-tuning"
updated: "2026-07-09"
---

# Fine-tuning

**Fine-tuning further trains a pretrained model on your own examples so it adapts to a specific task, tone, or format.**

**Fine-tuning** takes an already-trained model and continues training it on a smaller, curated dataset of your examples. The result is a model that better matches a particular style, domain, or output format.

Fine-tuning changes the model's weights, so it is heavier than prompting or RAG. Teams often reach for RAG first (to add knowledge) and fine-tune mainly to shape behavior or format that prompting alone cannot pin down.

## Related terms

- [Retrieval-augmented generation (RAG)](/glossary/ai-and-llms/retrieval-augmented-generation.md)
- [Large language model (LLM)](/glossary/ai-and-llms/large-language-model.md)

[AI & LLMs](/glossary/ai-and-llms.md) · [All glossary terms](/glossary.md)

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon`](/api/graphcanon)
- LLM index: [/llms.txt](/llms.txt)
- Full corpus: [/llms-full.txt](/llms-full.txt)

_GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_