AWD-LSTM+Behaviorial-Gating
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 Southern California
- Organisation type
- Academia
- Country
- United States of America
- Published
- 31 August 2019
- Authors
- Prashanth Gurunath Shivakumar, Shao-Yen Tseng, Panayiotis Georgiou, Shrikanth Narayanan
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.
- Parameters
- 27M
- Training data
- 929,000 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
- Confident
- Benchmark data
- AWD-LSTM+Behaviorial-Gating
Sources
Where this record came from and when it was last checked.
- Reference
- Behavior Gated Language Models
- Last updated
- 28 November 2025
What the numbers mean
About this model
AWD-LSTM+Behaviorial-Gating was published by University of Southern California, in United States of America, in August 2019. It comes out of academia.
It works in Language, and is recorded as doing language 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 929,000 tokens of text.
Answers
AWD-LSTM+Behaviorial-Gating — common questions
Who created AWD-LSTM+Behaviorial-Gating?
AWD-LSTM+Behaviorial-Gating was published by University of Southern California, based in United States of America, categorised as academia.
When was AWD-LSTM+Behaviorial-Gating released?
AWD-LSTM+Behaviorial-Gating was published in August 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 AWD-LSTM+Behaviorial-Gating used for?
AWD-LSTM+Behaviorial-Gating works in Language, and is recorded as handling language modeling. A model can carry several of each, so these are the areas it was built for rather than a limit on what it will attempt.
What GPU do I need to run AWD-LSTM+Behaviorial-Gating?
None. AWD-LSTM+Behaviorial-Gating 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 AWD-LSTM+Behaviorial-Gating open source?
No. AWD-LSTM+Behaviorial-Gating has not had its weights published, so it exists only as a service controlled by its owner.
How many parameters does AWD-LSTM+Behaviorial-Gating have?
AWD-LSTM+Behaviorial-Gating has 27M parameters. 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.