SRN-Encoded Grammatical Structures
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 California San Diego
- Organisation type
- Academia
- Country
- United States of America
- Published
- 1 September 1991
- Authors
- J. L. Elman
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Language
- Task
- Language Structure 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
- 177,800 tokens
4 training sets of 10k sentences each. Total number of words calculated by multiplying 10k and the avg. number of words per sentence in the training set.
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Citations
- 1,717
Sources
Where this record came from and when it was last checked.
- Reference
- Distributed representations, simple recurrent networks, and grammatical structure
- Last updated
- 28 November 2025
What the numbers mean
Where it came from
SRN-Encoded Grammatical Structures was published by University of California San Diego, in United States of America, in September 1991. academia is the category the publisher falls under.
It works in Language, and is recorded as doing language Structure Modeling.
Its weights were never published, so it can only be reached through its provider. No graphics card changes that.
How it was trained
It was trained on about 177,800 tokens of text.
Answers
SRN-Encoded Grammatical Structures — common questions
What GPU do I need to run SRN-Encoded Grammatical Structures?
None. SRN-Encoded Grammatical Structures 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 SRN-Encoded Grammatical Structures open source?
The licensing for SRN-Encoded Grammatical Structures 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 SRN-Encoded Grammatical Structures have?
No parameter count has been published for SRN-Encoded Grammatical Structures, which is why no memory or speed figure appears on this page.
Who created SRN-Encoded Grammatical Structures?
SRN-Encoded Grammatical Structures was published by University of California San Diego, based in United States of America, categorised as academia.
When was SRN-Encoded Grammatical Structures released?
SRN-Encoded Grammatical Structures was published in September 1991. 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 SRN-Encoded Grammatical Structures used for?
SRN-Encoded Grammatical Structures works in Language, and is recorded as handling language Structure Modeling. Models frequently carry more than one of each, and the tags describe purpose rather than capability limits.
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.