GLOSSARY
Fine-tuning
Additional training that adapts a pre-trained model to a specific style, task or domain, using your own examples.
Fine-tuning takes a pre-trained model and continues training it on curated examples — your company's support tickets, an artist's portfolio, code in your house style — so its outputs specialize. It is how generic models become brand voices, domain experts or task specialists.
Modern practice offers cheaper alternatives: prompting with examples ('few-shot'), and retrieval systems that inject facts at answer time. Fine-tuning still wins when you need consistent style at volume or a behavior prompts cannot reliably induce — and platforms from OpenAI to Leonardo.AI and Replicate make it self-serve.