Grown to Prune Two-layer stacked LSTM
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 Chicago,Toyota Technological Institute at Chicago
- Organisation type
- Academia,Academia
- Country
- United States of America
- Published
- 30 July 2020
- Authors
- Xin Yuan, Pedro Savarese, Michael Maire
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
- Unreleased
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
- 51
- Benchmark data
- Grown to Prune Two-layer stacked LSTM
Sources
Where this record came from and when it was last checked.
- Reference
- Growing Efficient Deep Networks by Structured Continuous Sparsification
- Last updated
- 1 January 2026
What the numbers mean
About this model
Grown to Prune Two-layer stacked LSTM was published by University of Chicago,Toyota Technological Institute at Chicago, in United States of America, in July 2020. academia,Academia is the category the publisher falls under.
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
Grown to Prune Two-layer stacked LSTM — common questions
Is Grown to Prune Two-layer stacked LSTM open source?
No. Grown to Prune Two-layer stacked LSTM has not had its weights published, so it exists only as a service controlled by its owner.
How many parameters does Grown to Prune Two-layer stacked LSTM have?
No parameter count has been published for Grown to Prune Two-layer stacked LSTM, which is why no memory or speed figure appears on this page.
Who created Grown to Prune Two-layer stacked LSTM?
Grown to Prune Two-layer stacked LSTM was published by University of Chicago,Toyota Technological Institute at Chicago, based in United States of America, categorised as academia,Academia.
When was Grown to Prune Two-layer stacked LSTM released?
Grown to Prune Two-layer stacked LSTM was published in July 2020. 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 Grown to Prune Two-layer stacked LSTM used for?
Grown to Prune Two-layer stacked LSTM works in Language, and is recorded as handling language modeling. Models frequently carry more than one of each, and the tags describe purpose rather than capability limits.
What GPU do I need to run Grown to Prune Two-layer stacked LSTM?
None. Grown to Prune Two-layer stacked LSTM 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.
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.