AI models
EGRU (WT2)
Training compute
2.2×10¹⁸ FLOP
Parameters
74M
Published
Jun 13, 2022
EGRU (WT2) is an AI model developed by Ruhr University Bochum, Technische Universität Dresden and University of London (Germany and United Kingdom), first published in June 2022. It works in the language domain, on tasks such as language modeling.
Training it took an estimated 2.2×10¹⁸ FLOP of compute (estimation method: operation counting). The model has 74,000,000 parameters. It was trained on roughly 2M datapoints. Training ran on NVIDIA A100.
Access: Unreleased. Its weights are not openly released. The reference paper has 34 citations. Epoch AI rates the confidence of this record as confident.
Full record
- Organization
- Ruhr University Bochum, Technische Universität Dresden, University of London
- Country of organization
- Germany, United Kingdom
- Domain
- Language
- Task
- Language modeling
- Training compute
- 2.2×10¹⁸ FLOP
- Compute estimation method
- Operation counting
- Parameters
- 74,000,000
- Dataset size
- 2M
- Training hardware
- NVIDIA A100
- Model accessibility
- Unreleased
- Open weights
- No
- Citations
- 34
- Epoch confidence
- Confident
More from Ruhr University Bochum,Technische Universität Dresden,University of London
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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