ResearchTrend.AI
One QuantLLM for ALL: Fine-tuning Quantized LLMs Once for Efficient Deployments

One QuantLLM for ALL: Fine-tuning Quantized LLMs Once for Efficient Deployments

Ke Yi
Yuhui Xu
Heng Chang
Chen Tang
Yuan Meng
Tong Zhang
Jia Li
    MQ
ArXivPDFHTML

Papers citing "One QuantLLM for ALL: Fine-tuning Quantized LLMs Once for Efficient Deployments"

2 / 2 papers shown
Title
Rotated Runtime Smooth: Training-Free Activation Smoother for accurate INT4 inference
Rotated Runtime Smooth: Training-Free Activation Smoother for accurate INT4 inference
Ke Yi
Zengke Liu
Jianwei Zhang
Chengyuan Li
Tong Zhang
Junyang Lin
Jingren Zhou
MQ
48
1
0
30 Sep 2024
Evaluating the Generalization Ability of Quantized LLMs: Benchmark, Analysis, and Toolbox
Evaluating the Generalization Ability of Quantized LLMs: Benchmark, Analysis, and Toolbox
Yijun Liu
Yuan Meng
Fang Wu
Shenhao Peng
Hang Yao
Chaoyu Guan
Chen Tang
Xinzhu Ma
Zhi Wang
Wenwu Zhu
MQ
62
7
0
15 Jun 2024