PEFT-Factory: Unified Parameter-Efficient Fine-Tuning of Autoregressive Large Language Models

The article introduces PEFT-Factory, a method for parameter-efficient fine-tuning (PEFT) of autoregressive large language models (LLMs). This suggests a focus on improving the efficiency of training LLMs, likely by reducing the number of parameters that need to be updated during fine-tuning. The use of 'unified' implies a potential for a single framework to handle various PEFT techniques.