ai
LoRA
Low-Rank Adaptation
Definition
LoRA is a parameter-efficient fine-tuning method that injects trainable low-rank decomposition matrices into a frozen pre-trained model's weight matrices. Instead of updating all weights, only the small rank-decomposition matrices (typically 0.1–1% of parameters) are trained.
LoRA enables high-quality fine-tuning on a single GPU with minimal memory overhead and has become the dominant PEFT technique.
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