RSM
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
- Cerenaut
- Country
- Australia
- Published
- 28 May 2019
- Authors
- David Rawlinson, Abdelrahman Ahmed, Gideon Kowadlo
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Language
- Task
- Language modeling
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
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 source
code for PTB, Apache 2.0 license: https://github.com/Cerenaut/rsm
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Record confidence
- Unknown
- Citations
- 4
- Benchmark data
- RSM
Sources
Where this record came from and when it was last checked.
- Reference
- Learning distant cause and effect using only local and immediate credit assignment
- Last updated
- 25 May 2026
What the numbers mean
Where it came from
RSM was published by Cerenaut, in Australia, in May 2019.
It works in Language, and is recorded as doing language modeling.
This is a closed model: the trained values stayed with whoever produced them, and there is no local version to run.
Answers
RSM — common questions
What GPU do I need to run RSM?
None. RSM 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 RSM open source?
No. RSM has not had its weights published, so it exists only as a service controlled by its owner.
How many parameters does RSM have?
No parameter count has been published for RSM, which is why no memory or speed figure appears on this page.
Who created RSM?
RSM was published by Cerenaut, based in Australia.
When was RSM released?
RSM was published in May 2019. 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 RSM used for?
RSM works in Language, and is recorded as handling language modeling. These are the areas it was designed around; they describe intent rather than a hard boundary.
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.