SqueezeBERT

Parameters

51.1M

Published

Jun 10, 2020

SqueezeBERT is an AI model developed by University of California (UC) Berkeley (United States), first published in June 2020. It works in the language domain, on tasks such as text autocompletion.

Epoch AI has no training-compute estimate for this model. The model has 51,100,000 parameters.

The reference paper has 140 citations.

Full record

Organization: University of California (UC) Berkeley
Country of organization: United States
Domain: Language
Task: Text autocompletion
Parameters: 51,100,000
Citations: 140

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SourceEpoch AI, 'AI Models'. Published online at epoch.ai. Retrieved 2026-07-29 from https://epoch.ai/data/ai-models. Licensed under CC BY 4.0.

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