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Jul, 2024
大型语言模型的修补训练
Patch-Level Training for Large Language Models
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Chenze Shao, Fandong Meng, Jie Zhou
TL;DR
该研究论文介绍了一种新的大型语言模型的训练方法——补丁级别训练,通过将多个标记压缩为一个补丁来减少序列长度,从而显著降低了计算成本,而不影响模型性能。
Abstract
As
large language models
(LLMs) achieve remarkable progress in language understanding and generation, their
training efficiency
has become a critical concern. Traditionally, LLMs are trained to predict the next t
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