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Scaling Laws for Floating Point Quantization Training
v1v2v3 (latest)

Scaling Laws for Floating Point Quantization Training

5 January 2025
Xingwu Sun
Shuaipeng Li
Ruobing Xie
Weidong Han
Kan Wu
Zhen Yang
Yixing Li
An Wang
Shuai Li
Jinbao Xue
Yu Cheng
Yangyu Tao
Zhanhui Kang
C. Xu
Di Wang
Jie Jiang
    MQAIFin
ArXiv (abs)PDFHTML

Papers citing "Scaling Laws for Floating Point Quantization Training"

28 / 28 papers shown
Title
Low-Bit Quantization Favors Undertrained LLMs: Scaling Laws for
  Quantized LLMs with 100T Training Tokens
Low-Bit Quantization Favors Undertrained LLMs: Scaling Laws for Quantized LLMs with 100T Training Tokens
Xu Ouyang
Tao Ge
Thomas Hartvigsen
Zhisong Zhang
Haitao Mi
Dong Yu
MQ
144
5
0
26 Nov 2024
Scaling Laws for Precision
Scaling Laws for Precision
Tanishq Kumar
Zachary Ankner
Benjamin Spector
Blake Bordelon
Niklas Muennighoff
Mansheej Paul
Cengiz Pehlevan
Christopher Ré
Aditi Raghunathan
AIFinMoMe
96
29
0
07 Nov 2024
Hunyuan-Large: An Open-Source MoE Model with 52 Billion Activated
  Parameters by Tencent
Hunyuan-Large: An Open-Source MoE Model with 52 Billion Activated Parameters by Tencent
Xingwu Sun
Yanfeng Chen
Yanwen Huang
Ruobing Xie
Jiaqi Zhu
...
Zhanhui Kang
Yong Yang
Yuhong Liu
Di Wang
Jie Jiang
MoEALMELM
146
34
0
04 Nov 2024
A Comprehensive Study on Quantization Techniques for Large Language
  Models
A Comprehensive Study on Quantization Techniques for Large Language Models
Jiedong Lang
Zhehao Guo
Shuyu Huang
MQ
81
12
0
30 Oct 2024
Scaling Laws in Linear Regression: Compute, Parameters, and Data
Scaling Laws in Linear Regression: Compute, Parameters, and Data
Licong Lin
Jingfeng Wu
Sham Kakade
Peter L. Bartlett
Jason D. Lee
LRM
114
20
0
12 Jun 2024
Transformers are SSMs: Generalized Models and Efficient Algorithms
  Through Structured State Space Duality
Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality
Tri Dao
Albert Gu
Mamba
119
535
0
31 May 2024
Surge Phenomenon in Optimal Learning Rate and Batch Size Scaling
Surge Phenomenon in Optimal Learning Rate and Batch Size Scaling
Shuaipeng Li
Penghao Zhao
Hailin Zhang
Xingwu Sun
Hao Wu
...
Zheng Fang
Jinbao Xue
Yangyu Tao
Tengjiao Wang
Di Wang
66
9
0
23 May 2024
DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts
  Language Model
DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model
DeepSeek-AI
Aixin Liu
Bei Feng
Bin Wang
Bingxuan Wang
...
Zhuoshu Li
Zihan Wang
Zihui Gu
Zilin Li
Ziwei Xie
MoE
127
495
0
07 May 2024
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Shuming Ma
Hongyu Wang
Lingxiao Ma
Lei Wang
Wenhui Wang
Shaohan Huang
Lifeng Dong
Ruiping Wang
Jilong Xue
Furu Wei
MQ
88
231
0
27 Feb 2024
OLMo: Accelerating the Science of Language Models
OLMo: Accelerating the Science of Language Models
Dirk Groeneveld
Iz Beltagy
Pete Walsh
Akshita Bhagia
Rodney Michael Kinney
...
Jesse Dodge
Kyle Lo
Luca Soldaini
Noah A. Smith
Hanna Hajishirzi
OSLM
195
413
0
01 Feb 2024
Dolma: an Open Corpus of Three Trillion Tokens for Language Model
  Pretraining Research
Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research
Luca Soldaini
Rodney Michael Kinney
Akshita Bhagia
Dustin Schwenk
David Atkinson
...
Hanna Hajishirzi
Iz Beltagy
Dirk Groeneveld
Jesse Dodge
Kyle Lo
107
281
0
31 Jan 2024
Extreme Compression of Large Language Models via Additive Quantization
Extreme Compression of Large Language Models via Additive Quantization
Vage Egiazarian
Andrei Panferov
Denis Kuznedelev
Elias Frantar
Artem Babenko
Dan Alistarh
MQ
177
105
0
11 Jan 2024
FP8-LM: Training FP8 Large Language Models
FP8-LM: Training FP8 Large Language Models
Houwen Peng
Kan Wu
Yixuan Wei
Guoshuai Zhao
Yuxiang Yang
...
Zheng Zhang
Shuguang Liu
Joe Chau
Han Hu
Peng Cheng
MQ
105
44
0
27 Oct 2023
BitNet: Scaling 1-bit Transformers for Large Language Models
BitNet: Scaling 1-bit Transformers for Large Language Models
Hongyu Wang
Shuming Ma
Li Dong
Shaohan Huang
Huaijie Wang
Lingxiao Ma
Fan Yang
Ruiping Wang
Yi Wu
Furu Wei
MQ
74
117
0
17 Oct 2023
Revisiting Block-based Quantisation: What is Important for Sub-8-bit LLM
  Inference?
Revisiting Block-based Quantisation: What is Important for Sub-8-bit LLM Inference?
Cheng Zhang
Jianyi Cheng
Ilia Shumailov
George A. Constantinides
Yiren Zhao
MQ
65
10
0
08 Oct 2023
QuantEase: Optimization-based Quantization for Language Models
QuantEase: Optimization-based Quantization for Language Models
Kayhan Behdin
Ayan Acharya
Aman Gupta
Qingquan Song
Siyu Zhu
S. Keerthi
Rahul Mazumder
MQ
84
21
0
05 Sep 2023
NF4 Isn't Information Theoretically Optimal (and that's Good)
NF4 Isn't Information Theoretically Optimal (and that's Good)
Davis Yoshida
MQ
66
10
0
12 Jun 2023
QLoRA: Efficient Finetuning of Quantized LLMs
QLoRA: Efficient Finetuning of Quantized LLMs
Tim Dettmers
Artidoro Pagnoni
Ari Holtzman
Luke Zettlemoyer
ALM
154
2,611
0
23 May 2023
The case for 4-bit precision: k-bit Inference Scaling Laws
The case for 4-bit precision: k-bit Inference Scaling Laws
Tim Dettmers
Luke Zettlemoyer
MQ
95
234
0
19 Dec 2022
SmoothQuant: Accurate and Efficient Post-Training Quantization for Large
  Language Models
SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models
Guangxuan Xiao
Ji Lin
Mickael Seznec
Hao Wu
Julien Demouth
Song Han
MQ
207
839
0
18 Nov 2022
FP8 Formats for Deep Learning
FP8 Formats for Deep Learning
Paulius Micikevicius
Dusan Stosic
N. Burgess
Marius Cornea
Pradeep Dubey
...
Naveen Mellempudi
S. Oberman
Mohammad Shoeybi
Michael Siu
Hao Wu
BDLVLMMQ
145
139
0
12 Sep 2022
FP8 Quantization: The Power of the Exponent
FP8 Quantization: The Power of the Exponent
Andrey Kuzmin
M. V. Baalen
Yuwei Ren
Markus Nagel
Jorn W. T. Peters
Tijmen Blankevoort
MQ
71
86
0
19 Aug 2022
Training Compute-Optimal Large Language Models
Training Compute-Optimal Large Language Models
Jordan Hoffmann
Sebastian Borgeaud
A. Mensch
Elena Buchatskaya
Trevor Cai
...
Karen Simonyan
Erich Elsen
Jack W. Rae
Oriol Vinyals
Laurent Sifre
AI4TS
208
1,987
0
29 Mar 2022
Explaining Neural Scaling Laws
Explaining Neural Scaling Laws
Yasaman Bahri
Ethan Dyer
Jared Kaplan
Jaehoon Lee
Utkarsh Sharma
78
269
0
12 Feb 2021
Scaling Laws for Neural Language Models
Scaling Laws for Neural Language Models
Jared Kaplan
Sam McCandlish
T. Henighan
Tom B. Brown
B. Chess
R. Child
Scott Gray
Alec Radford
Jeff Wu
Dario Amodei
651
4,921
0
23 Jan 2020
QPyTorch: A Low-Precision Arithmetic Simulation Framework
QPyTorch: A Low-Precision Arithmetic Simulation Framework
Tianyi Zhang
Zhiqiu Lin
Guandao Yang
Christopher De Sa
MQ
58
66
0
09 Oct 2019
Attention Is All You Need
Attention Is All You Need
Ashish Vaswani
Noam M. Shazeer
Niki Parmar
Jakob Uszkoreit
Llion Jones
Aidan Gomez
Lukasz Kaiser
Illia Polosukhin
3DV
805
132,725
0
12 Jun 2017
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed
  Systems
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
Martín Abadi
Ashish Agarwal
P. Barham
E. Brevdo
Zhiwen Chen
...
Pete Warden
Martin Wattenberg
Martin Wicke
Yuan Yu
Xiaoqiang Zheng
289
11,150
0
14 Mar 2016
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