Definition
A parameter-efficient fine-tuning (PEFT) technique that freezes the base model weights and injects and trains only a small set of new, low-rank matrices.
In short: A parameter-efficient fine-tuning (PEFT) technique that freezes the base model weights and injects and trains only a small set of new, low-rank matrices.