LoRA

LoRA, or low-rank adaptation, is a parameter-efficient fine-tuning method that freezes a model's original weights and trains small low-rank matrices added to them, making customization far cheaper.

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

Also called Low-rank adaptation.