English(EN) The Embedding Table Was 72% of the Model

嵌入表精度是减小LLM规模的关键

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-11 03:00

一项近期实验探索了量化对Transformer模型的影响，发现嵌入表占模型参数的很大一部分（72%）。研究发现，独立量化嵌入表，特别是使用逐行缩放，可以在性能损失极小的情况下大幅减少字节数。这种方法可以将模型尺寸减小6.2倍，同时通过将释放的字节重新分配给计数表和缓存来维持甚至提高系统级性能。 AI

影响优化嵌入表量化可以显著减小模型尺寸而不牺牲性能，从而实现更广泛的部署。

排序理由该条目详细介绍了模型量化和参数分布实验的发现，这是一项研究级别的贡献。[lever_c_demoted from research: ic=1 ai=1.0]

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dev.to — LLM tag TIER_1 English(EN) · Seth Wheeler · 2026-09-11 03:00

嵌入表占模型的72%

<p>An earlier experiment in this series had established something slightly deflating about a small transformer: quantising the whole network to int8 is free, and the bytes you save are better spent on count tables than on network precision. That is a useful result and it invites …

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嵌入表占模型的72%

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