Language & LLMs

What Is Parameter-Efficient Fine-Tuning?

Parameter-efficient fine-tuning (PEFT) adapts a large pretrained model to new tasks by updating only a small number of parameters while keeping most of the original weights frozen. This greatly reduces memory and compute costs compared to full fine-tuning. Methods include LoRA, adapters, and prompt tuning.