We use a few cookies

Essential cookies keep the library working. With your permission, we'd also like to use analytics to see what's useful and improve the experience. Read our Privacy Policy or Cookie Policy.

Skip to main content
Home/e-Resources/Artificial Intelligence & Machine Learning/LLM-QAT: Data-Free Quantization Aware Training for Large Language Models
Conference ProceedingsArtificial Intelligence & Machine Learning

LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

2024

Checking your access to this record.

Abstract & Overview

Zechun Liu, Barlas Oguz, Changsheng Zhao, Ernie Chang, Pierre Stock, Yashar Mehdad, Yangyang Shi, Raghuraman Krishnamoorthi, Vikas Chandra. Findings of the Association for Computational Linguistics: ACL 2024. 2024.

Cite this record

Zechun Liu, Barlas Oğuz, Changsheng Zhao, Ernie Chang, Pierre Stock, Yashar Mehdad, et al. (2024). LLM-QAT: Data-Free Quantization Aware Training for Large Language Models. https://doi.org/10.18653/v1/2024.findings-acl.26

Copy in another style

Liu, Z., Oğuz, B., Zhao, C., Chang, E., Stock, P., Mehdad, Y., Shi, Y., Krishnamoorthi, R., & Chandra, V. (2024). LLM-QAT: Data-Free Quantization Aware Training for Large Language Models. https://doi.org/10.18653/v1/2024.findings-acl.26
Author names are used as deposited, so check their order before you submit.

Metadata is harvested from open-access indexes and can be incomplete. Check a citation against the published version before relying on it — see our open access & attribution policy.