"SmoothQuant: Accurate and Efficient Post-Training Quantization for Large ..."

Guangxuan Xiao et al. (2022)

> Home

Details and statistics

DOI: 10.48550/ARXIV.2211.10438

access: open

type: Informal or Other Publication

metadata version: 2023-11-10

- view
  - electronic edition via DOI (open access)
  authority control:
- export record
  dblp key:
  - journals/corr/abs-2211-10438
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/journals/corr/abs-2211-10438
Guangxuan Xiao, Ji Lin, Mickaël Seznec, Julien Demouth, Song Han:
SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models. CoRR abs/2211.10438 (2022)

manage site settings

To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.