DEQ-TrellisNet (WT-103)

Parameters

180M

Published

Sep 3, 2019

DEQ-TrellisNet (WT-103) is an AI model developed by Carnegie Mellon University (CMU) and Intel Labs (United States), first published in September 2019. It works in the language domain, on tasks such as language modeling/generation.

Epoch AI has no training-compute estimate for this model. The model has 180,000,000 parameters. It was trained on roughly 103M datapoints.

Access: Unreleased. Its weights are not openly released. The reference paper has 873 citations. Epoch AI rates the confidence of this record as confident.

Full record

Organization: Carnegie Mellon University (CMU), Intel Labs
Country of organization: United States
Domain: Language
Task: Language modeling/generation
Parameters: 180,000,000
Dataset size: 103M
Model accessibility: Unreleased
Open weights: No
Citations: 873
Epoch confidence: Confident

More from Carnegie Mellon University (CMU),Intel Labs

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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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