Supervised fine-tuning

Supervised fine-tuning is the stage of training in which a pretrained model learns from curated examples of inputs paired with ideal outputs, teaching it to follow instructions and respond in a desired format.

Supervised fine-tuning sits in the Models part of the Agentik {OS} glossary, which defines the words used to build and run AI agent systems.

Also called SFT.