2-layer skip-LSTM + dropout tuning (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
- DeepMind
- Organisation type
- Industry
- Country
- United Kingdom of Great Britain and Northern Ireland
- Published
- 23 May 2018
- Authors
- Gábor Melis, Charles Blundell, Tomáš Kočiský, Karl Moritz Hermann, Chris Dyer, Phil Blunsom
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Language
- Task
- Language modeling
- Base model
- AWD-LSTM
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
- 24M
- 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
- Confident
- Benchmark data
- 2-layer skip-LSTM + dropout tuning (PTB)
Sources
Where this record came from and when it was last checked.
- Reference
- Pushing the bounds of dropout
- Last updated
- 11 February 2026
What the numbers mean
About this model
2-layer skip-LSTM + dropout tuning (PTB) was published by DeepMind, in United Kingdom of Great Britain and Northern Ireland, in May 2018. industry is the category the publisher falls under.
It works in Language, and is recorded as doing language modeling.
Its starting point was AWD-LSTM — most models at this scale are adapted from an existing base rather than built from nothing.
Because the weights are not available, none of the hardware figures elsewhere on this site apply to it.
Answers
2-layer skip-LSTM + dropout tuning (PTB) — common questions
When was 2-layer skip-LSTM + dropout tuning (PTB) released?
2-layer skip-LSTM + dropout tuning (PTB) was published in May 2018. 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 2-layer skip-LSTM + dropout tuning (PTB) used for?
2-layer skip-LSTM + dropout tuning (PTB) 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.
What GPU do I need to run 2-layer skip-LSTM + dropout tuning (PTB)?
None. 2-layer skip-LSTM + dropout tuning (PTB) 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 2-layer skip-LSTM + dropout tuning (PTB) open source?
No. 2-layer skip-LSTM + dropout tuning (PTB) has not had its weights published, so it exists only as a service controlled by its owner.
How many parameters does 2-layer skip-LSTM + dropout tuning (PTB) have?
2-layer skip-LSTM + dropout tuning (PTB) has 24M 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.
Who created 2-layer skip-LSTM + dropout tuning (PTB)?
2-layer skip-LSTM + dropout tuning (PTB) was published by DeepMind, based in United Kingdom of Great Britain and Northern Ireland, categorised as industry.
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.