Low-Bit Quantization Favors Undertrained LLMs: Scaling Laws for Quantized LLMs with 100T Training Tokens

Fuente: arXiv

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Bibliographic Details
Main Authors:	Ouyang, Xu, Ge, Tao, Hartvigsen, Thomas, Zhang, Zhisong, Mi, Haitao, Yu, Dong
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Computation and Language
Online Access:	Acceder al recurso
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Internet

https://arxiv.org/abs/2411.17691