What AI says about PEFT (Parameter-Efficient Fine-Tuning)

PEFT (Parameter-Efficient Fine-Tuning) is a Hugging Face library designed to adapt large pretrained models to downstream tasks without full fine-tuning by updating only a small subset of parameters. It reduces computational and storage costs, enabling training and deployment of large language models on consumer hardware, and integrates with Transformers, Diffusers, and Accelerate for loading, training, and inference. The library provides various adaptation methods (e.g., adapters, LoRA, prefix tuning) and serves as a reference implementation for many fine-tuning techniques, with quickstart guides and method overviews.