GraphEC
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
- Sun Yat-sen University,National Supercomputing Center in Shenzhen,Chongqing University,Key Laboratory of Machine Intelligence and Advanced Computing
- Organisation type
- Academia,Government,Academia
- Country
- China
- Published
- 18 September 2024
- Authors
- Yidong Song, Qianmu Yuan, Sheng Chen, Yuansong Zeng, Huiying Zhao, Yuedong Yang
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Biology
- Task
- Enzyme 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
- 74,487 tokens
588 + 74,487 + 3,297 = 78,372 ≈ 7.8e4 datapoints GraphEC training data from: - Active Site: 588 - EC Number: 74,487 - Optimum pH: 3,297
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
- Accurately predicting enzyme functions through geometric graph learning on ESMFold-predicted structures
- Last updated
- 28 November 2025
What the numbers mean
About this model
GraphEC was published by Sun Yat-sen University,National Supercomputing Center in Shenzhen,Chongqing University,Key Laboratory of Machine Intelligence and Advanced Computing, in China, in September 2024. The organisation is categorised as academia,Government,Academia.
It works in Biology, and is recorded as doing enzyme function prediction.
This is a closed model: the trained values stayed with whoever produced them, and there is no local version to run.
What went into building it
The training set ran to roughly 74,487 tokens.
Answers
GraphEC — common questions
When was GraphEC released?
GraphEC 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 GraphEC used for?
GraphEC works in Biology, and is recorded as handling enzyme 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 GraphEC?
None. GraphEC 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 GraphEC open source?
The licensing for GraphEC 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 GraphEC have?
No parameter count has been published for GraphEC, which is why no memory or speed figure appears on this page.
Who created GraphEC?
GraphEC was published by Sun Yat-sen University,National Supercomputing Center in Shenzhen,Chongqing University,Key Laboratory of Machine Intelligence and Advanced Computing, based in China, categorised as academia,Government,Academia.
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.