Low-rank adaptation (LoRA)

loh-rah /ˈloʊrə

A method for adapting a large model to a new task by adding a small set of learnable changes, instead of retraining the entire model. LoRA is popular because it can be faster and cheaper, and it lets people create multiple specialised versions of a model while keeping the original base model unchanged.