DOC + Finetune∗ + Partial Shuffle (WT2)

Parameters

67.3M

Published

Mar 11, 2019

DOC + Finetune∗ + Partial Shuffle (WT2) is an AI model developed by University of Washington (United States), first published in March 2019. It works in the language domain, on tasks such as language modeling.

Epoch AI has no training-compute estimate for this model. The model has 67,300,000 parameters.

Access: Unreleased. Its weights are not openly released. The reference paper has 6 citations.

Full record

Organization: University of Washington
Country of organization: United States
Domain: Language
Task: Language modeling
Parameters: 67,300,000
Model accessibility: Unreleased
Open weights: No
Citations: 6