AI models
ProteinDT
Published
Feb 9, 2023
ProteinDT is an AI model developed by University of California (UC) Berkeley, California Institute of Technology, University of Toronto, University of Wisconsin Madison, Texas A&M, NVIDIA and Mila - Quebec AI (originally Montreal Institute for Learning Algorithms) (United States and Canada), first published in February 2023. It works in the biology and language domain, on tasks such as proteins, protein representation learning, protein generation and protein design.
Epoch AI has no training-compute estimate for this model. It was trained on roughly 132.3M datapoints.
Access: Open weights (unrestricted). Its weights are openly available. It is built on top of SciBERT. Epoch AI rates the confidence of this record as likely.
Full record
- Organization
- University of California (UC) Berkeley, California Institute of Technology, University of Toronto, University of Wisconsin Madison, Texas A&M, NVIDIA, Mila - Quebec AI (originally Montreal Institute for Learning Algorithms)
- Country of organization
- United States, Canada
- Domain
- Biology, Language
- Task
- Proteins, Protein representation learning, Protein generation, Protein design
- Dataset size
- 132.3M
- Numerical format
- FP16
- Model accessibility
- Open weights (unrestricted)
- Open weights
- Yes
- Base model
- SciBERT
- 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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