Parameter-Efficient Fine-Tuning (PEFT) methods like LoRA reduce compute costs for adapting large models.
- True
- False
Answer: True
PEFT methods (LoRA, Adapter, Prefix-tuning) update small subset of parameters or add lightweight modules, reducing compute/memory vs full fine-tuning. Critical for resource-constrained LLM adaptation.