Parameter-efficient fine-tuning

Parameter-efficient fine-tuning is a family of methods that adapt a large model by training only a small number of added or selected parameters, greatly reducing memory and compute costs.

Parameter-efficient 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 PEFT.