ProTeM
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
- Zhejiang Lab,Zhejiang University (ZJU),Huazhong University of Science and Technology,Mohamed bin Zayed University of Artificial Intelligence (MBZUAI)
- Organisation type
- Academia,Academia,Academia
- Country
- China, United Arab Emirates
- Published
- 17 September 2024
- Authors
- Ming Qin, Xun Li, Yuhao Wang, Zhenping Li, Hongbin Ye, Zongbing Wang, Weihao Gao, Shangsong Liang, Qiang Zhang, Keyan Ding
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Biology
- Task
- Protein function prediction
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.
- Training data
- tokens
Bio-LLM: 2,000,000 documents × 100 tokens = 2.0 × 10^8 tokens ProTeM: 467,277 pairs × (50 text + 300 protein) tokens = 1.63 × 10^8 tokens Total: 2.0 × 10^8 + 1.63 × 10^8 = 3.63 × 10^8 tokens
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Record confidence
- Confident
Sources
Where this record came from and when it was last checked.
- Reference
- ProTeM: Unifying Protein Function Prediction via Text Matching
- Last updated
- 28 November 2025
What the numbers mean
About this model
ProTeM was published by Zhejiang Lab,Zhejiang University (ZJU),Huazhong University of Science and Technology,Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), in China, in September 2024. academia,Academia,Academia is the category the publisher falls under.
It works in Biology, and is recorded as doing protein function prediction.
This is a closed model: the trained values stayed with whoever produced them, and there is no local version to run.
Answers
ProTeM — common questions
Who created ProTeM?
ProTeM was published by Zhejiang Lab,Zhejiang University (ZJU),Huazhong University of Science and Technology,Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), based in China, categorised as academia,Academia,Academia.
When was ProTeM released?
ProTeM was published in September 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 ProTeM used for?
ProTeM works in Biology, and is recorded as handling protein function prediction. Models frequently carry more than one of each, and the tags describe purpose rather than capability limits.
What GPU do I need to run ProTeM?
None. ProTeM 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.
Is ProTeM open source?
The licensing for ProTeM 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 ProTeM have?
No parameter count has been published for ProTeM, which is why no memory or speed figure appears on this page.
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.