Sebastian Raschka • 4/12/2023

Understanding Parameter-Efficient Finetuning of Large Language Models: From Prefix Tuning to LLaMA-Adapters

This technical article details parameter-efficient finetuning (PEFT) techniques for adapting large language models (LLMs). It covers the benefits of PEFT, explains core methods like prompt tuning, prefix tuning, and adapters, and provides a focused look at the recent LLaMA-Adapter method for efficient model training on limited hardware.

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#large language models #Parameter Efficient Finetuning #Prefix Tuning