ProtTrans
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A to Z
- A · App
- No
- B · Built By
- TU Munich
- C · CEO & Politics
- N/A (academic research) — No public partisan activity documented
- D · Date
- 2021
- E · Expertise
- Intermediate+
- F · Free Tier
- Yes
- G · Generates
- Text only
- H · Deployment
- Cloud + Local (open weights)
- I · Inputs
- Text
- J · Jurisdiction
- Germany
- K · Key Staffers
- Ahmed Elnaggar (Lead author), Michael Heinzinger (Co-lead author), Burkhard Rost (Senior author)
- L · Languages
- English-primary
- M · Model Type
- Science/Biology
- N · Safety Issues
- None reported
- O · Open Source
- Yes — open weights
- P · Pricing
- Free (open source, MIT)
- Q · AIDb Rating
- [UNKNOWN]
- R · What Makes It Special
- ProtTrans, protein language models: two autoregressive models (Transformer-XL, XLNet) and four autoencoder models (BERT, ALBERT, ELECTRA, T5) trained on up to 393 billion amino acids from UniRef and BFD using the Summit supercomputer and TPU pods; the best embeddings (ProtT5) were the first to beat the state of the art in protein secondary-structure prediction without evolutionary information.
- S · Stock / Status
- University
- T · Training Cutoff
- [UNKNOWN]
- U · Users
- [UNKNOWN]
- V · Voice Chat
- No
- W · Weights
- Downloadable
- X · X Handle
- [UNKNOWN]
- Y · Year Founded
- [UNKNOWN]
- Z · Bottom Line
- Open-weights Science/Biology from TU Munich, released 2021.
Data completeness 81% · Last verified 2026-05-12 · Primary source ↗
Cite this
“ProtTrans.” AIDb — The AI Database. Verified 2026-05-12. https://theaidatabase.com/m/prottrans.html