AI models
Tensorized Transformer (PTB)
Training compute
2×10¹⁵ FLOP
Parameters
12M
Published
Jun 24, 2019
Tensorized Transformer (PTB) is an AI model developed by Tianjin University, Microsoft Research Asia and Beijing Institute of Technology (China), first published in June 2019. It works in the language domain, on tasks such as language modeling and translation.
Training it took an estimated 2×10¹⁵ FLOP of compute. The model has 12,000,000 parameters. Training ran on 2 NVIDIA P40.
Access: Unreleased. Its weights are not openly released. The reference paper has 194 citations. Epoch AI rates the confidence of this record as confident.
Full record
- Organization
- Tianjin University, Microsoft Research Asia, Beijing Institute of Technology
- Country of organization
- China
- Domain
- Language
- Task
- Language modeling, Translation
- Training compute
- 2×10¹⁵ FLOP
- Parameters
- 12,000,000
- Training hardware
- NVIDIA P40
- Chips used
- 2
- Training power draw
- 1.0 kW
- Model accessibility
- Unreleased
- Open weights
- No
- Citations
- 194
- Epoch confidence
- Confident
More from Tianjin University,Microsoft Research Asia,Beijing Institute of Technology
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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