AWD-LSTM+WT+Cache+IOG (PTB)
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
- NTT Communication Science Laboratories
- Organisation type
- Industry
- Country
- Japan
- Published
- 26 September 2017
- Authors
- Sho Takase, Jun Suzuki, Masaaki Nagata
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
- 30M
- 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
- Open (non-commercial)
license, looks non-commercial: https://github.com/nttcslab-nlp/iog?tab=License-1-ov-file#readme https://github.com/nttcslab-nlp/iog
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+WT+Cache+IOG (PTB)
Sources
Where this record came from and when it was last checked.
- Reference
- Input-to-Output Gate to Improve RNN Language Models
- Last updated
- 11 February 2026
What the numbers mean
Background
AWD-LSTM+WT+Cache+IOG (PTB) was published by NTT Communication Science Laboratories, in the country recorded as Japan, during September 2017. The category the publisher falls under is industry.
It works in the domain of Language, and is recorded as performing the task of language modeling.
Because the weights are not available, none of the hardware figures elsewhere on this site apply to it.
What went into building it
The training set ran to roughly 929,000 tokens of text.
Answers
AWD-LSTM+WT+Cache+IOG (PTB) — common questions
AWD-LSTM+WT+Cache+IOG (PTB)— is it open source?
No. Its weights have not been published, so it exists only as a service controlled by its owner.
AWD-LSTM+WT+Cache+IOG (PTB)— how many parameters does it have?
It has a parameter count of 30M. 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.
AWD-LSTM+WT+Cache+IOG (PTB)— who created it?
It was published by NTT Communication Science Laboratories, based in Japan, an organisation categorised as industry.
AWD-LSTM+WT+Cache+IOG (PTB)— when was it released?
It was published in September 2017. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
AWD-LSTM+WT+Cache+IOG (PTB)— what is it used for?
It works in the domain of Language, and is recorded as handling the task of language modeling. These are the areas it was designed around; they describe intent rather than a hard boundary.
AWD-LSTM+WT+Cache+IOG (PTB)— what GPU do I need to run it?
None. This 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.