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deployment

PEFT

Parameter-Efficient Fine-Tuning, a family of techniques that adapt large models by training only a small subset of parameters. PEFT methods include LoRA, adapters, and prefix tuning, making fine-tuning accessible with limited compute resources.

In practice

PEFT can adapt a foundation model to a new domain by training only 1% of the total parameters.