Parameter-Efficient Fine-Tuning (PEFT): Fine-tune Large Language Models with Limited Resources

Comperhishive Introduction to Parameter-Efficient Fine-Tuning (PEFT)

Parameter-efficient fine-tuning (PEFT) methods, such as LoRA, provide a cost-effective approach for refining substantial language models, utilizing only a fraction of their parameters.

This obviates the need for resource-intensive complete fine-tuning and facilitates training with constrained computational resources. PEFT’s modular…