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Computer Science > Machine Learning

arXiv:2407.09577v1 (cs)
[Submitted on 12 Jul 2024 (this version) , latest version 1 Jun 2025 (v3) ]

Title: Flash normalization: fast RMSNorm for LLMs

Title: 快速 RMSNorm 用于 LLMs 的归一化

Authors:Nils Graef, Matthew Clapp, Andrew Wasielewski
Abstract: RMSNorm is used by many LLMs such as Llama, Mistral, and OpenELM. This paper details FlashNorm, which is an exact but faster implementation of RMSNorm followed by linear layers. See https://huggingface.co/open-machine/FlashNorm for code and more transformer tricks.
Abstract: RMSNorm被许多大型语言模型如Llama、Mistral和OpenELM所使用。 本文详细介绍了FlashNorm,这是RMSNorm的一种精确但更快的实现,随后是线性层。 请访问https://huggingface.co/open-machine/FlashNorm查看代码和更多变换器技巧。
Comments: 7 pages, 8 figures
Subjects: Machine Learning (cs.LG)
Cite as: arXiv:2407.09577 [cs.LG]
  (or arXiv:2407.09577v1 [cs.LG] for this version)
  https://doi.org/10.48550/arXiv.2407.09577
arXiv-issued DOI via DataCite

Submission history

From: Nils Graef [view email]
[v1] Fri, 12 Jul 2024 00:37:55 UTC (440 KB)
[v2] Tue, 1 Apr 2025 23:19:22 UTC (449 KB)
[v3] Sun, 1 Jun 2025 22:12:10 UTC (584 KB)
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