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Training Recipe for N:M Structured Sparsity with Decaying Pruning Mask

Training Recipe for N:M Structured Sparsity with Decaying Pruning Mask

15 September 2022
Sheng-Chun Kao
Amir Yazdanbakhsh
Suvinay Subramanian
Shivani Agrawal
Utku Evci
T. Krishna
ArXivPDFHTML

Papers citing "Training Recipe for N:M Structured Sparsity with Decaying Pruning Mask"

5 / 5 papers shown
Title
SLoPe: Double-Pruned Sparse Plus Lazy Low-Rank Adapter Pretraining of LLMs
SLoPe: Double-Pruned Sparse Plus Lazy Low-Rank Adapter Pretraining of LLMs
Mohammad Mozaffari
Amir Yazdanbakhsh
Zhao Zhang
M. Dehnavi
65
5
0
28 Jan 2025
Effective Interplay between Sparsity and Quantization: From Theory to Practice
Effective Interplay between Sparsity and Quantization: From Theory to Practice
Simla Burcu Harma
Ayan Chakraborty
Elizaveta Kostenok
Danila Mishin
Dongho Ha
...
Martin Jaggi
Ming Liu
Yunho Oh
Suvinay Subramanian
Amir Yazdanbakhsh
MQ
29
4
0
31 May 2024
I-BERT: Integer-only BERT Quantization
I-BERT: Integer-only BERT Quantization
Sehoon Kim
A. Gholami
Z. Yao
Michael W. Mahoney
Kurt Keutzer
MQ
86
336
0
05 Jan 2021
Comparing Rewinding and Fine-tuning in Neural Network Pruning
Comparing Rewinding and Fine-tuning in Neural Network Pruning
Alex Renda
Jonathan Frankle
Michael Carbin
222
382
0
05 Mar 2020
Q-BERT: Hessian Based Ultra Low Precision Quantization of BERT
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
225
571
0
12 Sep 2019
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