Online event: Scaling Down to Scale Up: A Guide to PEFT

How to RLHF #LLAMA if you don't have hundreds of GPUS? Do it in a parameter-efficient way. Vladislav will share parameter-efficient fine-tuning #PEFT survey! [http://arxiv.org/abs/2303.15647](https://t.co/R8w1DVZXJi)

This paper presents a systematic overview and comparison of parameter-efficient fine-tuning methods covering over 40 papers published between February 2019 and February 2023. These methods aim to resolve the infeasibility and impracticality of fine-tuning large language models by only training a small set of parameters. We provide a taxonomy that covers a broad range of methods and present a detailed method comparison with a specific focus on real-life efficiency and fine-tuning multibillion-scale language models.

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