SeaMoon
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
- Sorbonne University,Université Grenoble Alpes,Institut Universitaire de France (IUF)
- Organisation type
- Academia,Academia,Research collective
- Country
- France
- Published
- 25 September 2024
- Authors
- Valentin Lombard, Dan Timsit, Sergei Grudinin, Elodie Laine
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Biology
- Task
- Protein folding 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.
- Parameters
- 1M
- Training data
- tokens
- Epochs
- 500
7,339 collections × 5 conformations/collection = 36,695 conformations 36,695 conformations × 300 residues/protein = 11,008,500 datapoints Final estimate: 1.1e7 datapoints
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Record confidence
- Likely
Sources
Where this record came from and when it was last checked.
- Reference
- SeaMoon: Prediction of molecular motions based on language models
- Last updated
- 28 November 2025
What the numbers mean
Where it came from
SeaMoon was published by Sorbonne University,Université Grenoble Alpes,Institut Universitaire de France (IUF), in the country recorded as France, during September 2024. The publishing organisation is categorised as academia,Academia,Research collective.
It works in the domain of Biology, and is recorded as performing the task of protein folding prediction.
Because the weights are not available, none of the hardware figures elsewhere on this site apply to it.
Answers
SeaMoon — common questions
SeaMoon— who created it?
It was published by Sorbonne University,Université Grenoble Alpes,Institut Universitaire de France (IUF), based in France, an organisation categorised as academia,Academia,Research collective.
SeaMoon— when was it released?
It 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.
SeaMoon— what is it used for?
It works in the domain of Biology, and is recorded as handling the task of protein folding prediction. Models frequently carry more than one of each, and the tags describe purpose rather than capability limits.
SeaMoon— what GPU do I need to run it?
None. This 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.
SeaMoon— is it open source?
The licensing was never recorded in our source data. We treat unstated licensing as closed, because an unrecorded licence is not one to rely on.
SeaMoon— how many parameters does it have?
It has a parameter count of 1M. 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.
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.