FPTQ: Fine-grained Post-Training Quantization for Large Language Models

30 August 2023

Papers citing "FPTQ: Fine-grained Post-Training Quantization for Large Language Models"

4 / 4 papers shown

Title
RepQuant: Towards Accurate Post-Training Quantization of Large Transformer Models via Scale Reparameterization Zhikai Li Xuewen Liu Jing Zhang Qingyi Gu MQ 27 7 0 08 Feb 2024
ZeroQuant-V2: Exploring Post-training Quantization in LLMs from Comprehensive Study to Low Rank Compensation Z. Yao Xiaoxia Wu Cheng-rong Li Stephen Youn Yuxiong He MQ 63 56 0 15 Mar 2023
The Pile: An 800GB Dataset of Diverse Text for Language Modeling Leo Gao Stella Biderman Sid Black Laurence Golding Travis Hoppe ... Horace He Anish Thite Noa Nabeshima Shawn Presser Connor Leahy AIMat 245 1,977 0 31 Dec 2020
Q-BERT: Hessian Based Ultra Low Precision Quantization of BERT Sheng Shen Zhen Dong Jiayu Ye Linjian Ma Z. Yao A. Gholami Michael W. Mahoney Kurt Keutzer MQ 217 571 0 12 Sep 2019