Prot2Token
No estimate
No hardware requirements for this model
The weights for this model have not been published, so it cannot be downloaded or run on your own hardware at any size. It is reachable only through its provider, and no graphics card changes that.
On record
Full specification
Everything on record for this model. Most of it describes how it was trained rather than how it runs — useful context for judging how much work went into it, and how it compares with models built at a different scale.
Origin
Who built this model, where, and when it was published.
- Organisation
- University of Missouri,Politecnico di Milano
- Organisation type
- Academia
- Country
- United States of America, Italy
- Published
- 3 June 2024
- Authors
- Mahdi Pourmirzaei, Farzaneh Esmaili, Mohammadreza Pourmirzaei, Duolin Wang, Dong Xu
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Biology
- Task
- Protein or nucleotide language model (pLM/nLM)
- Base model
- ESM2-650M
Size
How large the model is and how much data it was trained on. Parameters are the figure that decides whether it fits on a given graphics card.
- Parameters
- 650M
- Training data
- tokens
- Epochs
- 16
1,024,055 = 8,678 + 53,571 + 21,446 + 15,550 + 29,898 + 12,312 + 29,215 + 23,604 + 35,669 + 8,716 + 300,700 + 6,391 + 16,436 + 22,841 + 10,400 + 428,628 307,216,500 = 1,024,055 × 300 Final estimate: 3.1 × 10⁸
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Record confidence
- Confident
- Citations
- 10
Sources
Where this record came from and when it was last checked.
- Reference
- Prot2Token: A multi-task framework for protein language processing using autoregressive language modeling
- Last updated
- 28 November 2025
What the numbers mean
Where it came from
Prot2Token was published by University of Missouri,Politecnico di Milano, in United States of America, in June 2024. academia is the category the publisher falls under.
It works in Biology, and is recorded as doing protein or nucleotide language model (pLM/nLM).
It builds on ESM2-650M, which is why it shares that model's general shape and size.
This is a closed model: the trained values stayed with whoever produced them, and there is no local version to run.
Answers
Prot2Token — common questions
Is Prot2Token open source?
The licensing for Prot2Token was never recorded in our source data. We treat unstated licensing as closed, because an unrecorded licence is not one to rely on.
How many parameters does Prot2Token have?
Prot2Token has 650M parameters. That figure is the total, and it is what decides how much memory the model needs — roughly half a gigabyte per billion at the compression most people use.
Who created Prot2Token?
Prot2Token was published by University of Missouri,Politecnico di Milano, based in United States of America, categorised as academia.
When was Prot2Token released?
Prot2Token was published in June 2024. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
What is Prot2Token used for?
Prot2Token works in Biology, and is recorded as handling protein or nucleotide language model (pLM/nLM). These are the areas it was designed around; they describe intent rather than a hard boundary.
What GPU do I need to run Prot2Token?
None. Prot2Token is a closed model — its weights were never published, so it cannot be downloaded or run on your own hardware at any price. It is reachable only through its provider.
The other direction
Looking at it from the other side?
This page starts from the model. If you already own a card and want to know everything it will run, start from the hardware instead.