AI models
Fraternal dropout + AWD-LSTM 3-layer (PTB)
Training compute
7×10¹⁶ FLOP
Parameters
24M
Published
Oct 31, 2017
Fraternal dropout + AWD-LSTM 3-layer (PTB) is an AI model developed by University of Montreal / Université de Montréal and Mila - Quebec AI (originally Montreal Institute for Learning Algorithms) (Canada), first published in October 2017. It works in the language domain, on tasks such as language modeling.
Training it took an estimated 7×10¹⁶ FLOP of compute. The model has 24,000,000 parameters. It was trained on roughly 929K datapoints.
Access: Unreleased. Its weights are not openly released. Epoch AI rates the confidence of this record as confident.
Full record
- Organization
- University of Montreal / Université de Montréal, Mila - Quebec AI (originally Montreal Institute for Learning Algorithms)
- Country of organization
- Canada
- Domain
- Language
- Task
- Language modeling
- Training compute
- 7×10¹⁶ FLOP
- Parameters
- 24,000,000
- Dataset size
- 929K
- Model accessibility
- Unreleased
- Open weights
- No
- Epoch confidence
- Confident
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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