Efficient Pretraining and Finetuning of Quantized LLMs with Low-Rank Structure-Reference-Cited by-同舟云学术

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Efficient Pretraining and Finetuning of Quantized LLMs with Low-Rank Structure

Published:2024-07-23 Issue: Volume:36 Page:300-311
ISSN:
Container-title:2024 IEEE 44th International Conference on Distributed Computing Systems (ICDCS)
language:
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Author:

Liu Xiao-Yang¹,Zhang Jie²,Wang Guoxuan³,Tong Weiqin²,Walid Anwar⁴

Affiliation:

1. Rensselaer Polytechnic Institute,Department of Computer Science

2. School of Computer Engineering and Science, Shanghai University

3. Whiting School of Engineering, Johns Hopkins University,Department of Computer Science

4. Columbia University,Department of Electrical Engineering

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10630852/10630896/10631087.pdf?arnumber=10631087

Reference43 articles.

1. LoRA: Low-rank adaptation of large language models;Edward,2022

2. QLoRA: Efficient finetuning of quantized llms;Dettmers;Advances in Neural Information Processing Systems,2024

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