STEPS
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
- McGill University,Mila - Quebec AI (originally Montreal Institute for Learning Algorithms),Baidu Research - Silicon Valley AI Lab,Baidu,Boston Consulting Group X
- Organisation type
- Academia,Academia,Industry,Industry,Industry
- Country
- Canada, United States of America, China
- Published
- 1 April 2023
- Authors
- Can (Sam) Chen, Jingbo Zhou, Fan Wang, Xue Liu, Dejing Dou
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Biology
- Task
- Protein classification, Protein localization prediction, Enzyme-catalyzed reaction classification
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
40,000 proteins × 300 residues/protein = 12,000,000 residues Total Unique Data Points = 12,000,000
Availability
Whether you can obtain the model and run it on your own hardware, which is what decides if any of the graphics-card figures on this page apply.
- Weights
- Closed — provider access only
- Model access
- Unreleased
- Training code
- Open (non-commercial)
The Alphafold2 database is available in https://alphafold.ebi.ac.uk/. The PDB files are available in https://www.rcsb.org/. The downstream tasks are available in https://github.com/phermosilla/IEConv\_proteins/tree/master/Datasets. The code of the proposed method is available in https://github.com/GGchen1997/STEPS_Bioinformatics. no clear license
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
- 75
Sources
Where this record came from and when it was last checked.
- Reference
- Structure-aware protein self-supervised learning
- Last updated
- 1 December 2025
What the numbers mean
About this model
STEPS was published by McGill University,Mila - Quebec AI (originally Montreal Institute for Learning Algorithms),Baidu Research - Silicon Valley AI Lab,Baidu,Boston Consulting Group X, in Canada, in April 2023. It comes out of academia,Academia,Industry,Industry,Industry.
It works in Biology, and is recorded as doing protein classification, Protein localization prediction, Enzyme-catalyzed reaction classification.
This is a closed model: the trained values stayed with whoever produced them, and there is no local version to run.
Answers
STEPS — common questions
Who created STEPS?
STEPS was published by McGill University,Mila - Quebec AI (originally Montreal Institute for Learning Algorithms),Baidu Research - Silicon Valley AI Lab,Baidu,Boston Consulting Group X, based in Canada, categorised as academia,Academia,Industry,Industry,Industry.
When was STEPS released?
STEPS was published in April 2023. 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 STEPS used for?
STEPS works in Biology, and is recorded as handling protein classification, Protein localization prediction, Enzyme-catalyzed reaction classification. Models frequently carry more than one of each, and the tags describe purpose rather than capability limits.
What GPU do I need to run STEPS?
None. STEPS 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 STEPS open source?
No. STEPS has not had its weights published, so it exists only as a service controlled by its owner.
How many parameters does STEPS have?
No parameter count has been published for STEPS, 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.