AI models
R-Transformer
Training compute
8.6×10¹⁵ FLOP
Parameters
15.8M
Published
Jul 12, 2019
R-Transformer is an AI model developed by Michigan State University and TAL Education Group (Xueersi) (United States and China), first published in July 2019. It works in the language domain, on tasks such as language modeling.
Training it took an estimated 8.6×10¹⁵ FLOP of compute (estimation method: operation counting). The model has 15,800,000 parameters. It was trained on roughly 912.3K datapoints.
Access: Unreleased. Its weights are not openly released. The reference paper has 116 citations. Epoch AI rates the confidence of this record as likely.
Full record
- Organization
- Michigan State University, TAL Education Group (Xueersi)
- Country of organization
- United States, China
- Domain
- Language
- Task
- Language modeling
- Training compute
- 8.6×10¹⁵ FLOP
- Compute estimation method
- Operation counting
- Parameters
- 15,800,000
- Dataset size
- 912.3K
- Model accessibility
- Unreleased
- Open weights
- No
- Citations
- 116
- Epoch confidence
- Likely
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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