Restricted Bolzmann machines
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 Toronto
- Organisation type
- Academia
- Country
- Canada
- Published
- 20 June 2007
- Authors
- Russ Salukhutdinov, Andriy Mnih, GE Hinton
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Recommendation
- Task
- Movie ratings, Recommender system
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
- 100,480,507 tokens
The training data set consists of 100,480,507 ratings
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Citations
- 2,140
Sources
Where this record came from and when it was last checked.
- Reference
- Restricted Boltzmann machines for collaborative filtering
- Last updated
- 28 November 2025
What the numbers mean
Where it came from
Restricted Bolzmann machines was published by University of Toronto, in Canada, in June 2007. The organisation is categorised as academia.
It works in Recommendation, and is recorded as doing movie ratings, Recommender system.
Because the weights are not available, none of the hardware figures elsewhere on this site apply to it.
What went into building it
Around 100,480,507 tokens went into training it.
Answers
Restricted Bolzmann machines — common questions
How many parameters does Restricted Bolzmann machines have?
No parameter count has been published for Restricted Bolzmann machines, which is why no memory or speed figure appears on this page.
Who created Restricted Bolzmann machines?
Restricted Bolzmann machines was published by University of Toronto, based in Canada, categorised as academia.
When was Restricted Bolzmann machines released?
Restricted Bolzmann machines was published in June 2007. 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 Restricted Bolzmann machines used for?
Restricted Bolzmann machines works in Recommendation, and is recorded as handling movie ratings, Recommender system. These are the areas it was designed around; they describe intent rather than a hard boundary.
What GPU do I need to run Restricted Bolzmann machines?
None. Restricted Bolzmann machines 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 Restricted Bolzmann machines open source?
The licensing for Restricted Bolzmann machines was never recorded in our source data. We treat unstated licensing as closed, because an unrecorded licence is not one to rely on.
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.