Farhad Rahimi

Researcher

What is Parameter-efficient fine-tuning (PEFT)?

Parameter-efficient fine-tuning (PEFT) is a method of improving the performance of pretrained large language models (LLMs) and neural networks for specific tasks or data sets. By training a small set of parameters and preserving most of the large pretrained model’s structure, PEFT saves time and computational resources.