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Jun, 2024
基于学习的子空间投影器的通用GPU上超参微调LLM的实用卸载
Practical offloading for fine-tuning LLM on commodity GPU via learned subspace projectors
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Siyuan Chen, Zelong Guan, Yudong Liu, Phillip B. Gibbons
TL;DR
通过学习稀疏压缩器和新颖的分层通信调度,我们提出了一个离线框架 LSP_Offload,能够在普通硬件上以接近原生速度进行大型语言模型的微调,从而在受限的内存条件下显著提高微调吞吐量并缩短微调时间。
Abstract
fine-tuning
large language models (
llms
) requires significant memory, often exceeding the capacity of a single GPU. A common solution to this memory challenge is offloading compute and data from the GPU to the CP
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