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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.