Transformer-XL + FWL
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
- Google Research
- Organisation type
- Industry
- Country
- United States of America
- Published
- 5 December 2022
- Authors
- Kevin Clark, Kelvin Guu, Ming-Wei Chang, Panupong Pasupat, Geoffrey Hinton, Mohammad Norouzi
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Language
- Task
- Language modeling/generation
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
- 257M
- Training data
- 103,000,000 tokens
"For Transformer-XL, we use the large model (257M parameters)."
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 source
apache 2 for code: https://github.com/google-research/google-research/tree/master/fwl
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Citations
- 19
- Benchmark data
- TransformerXL + FWL
Sources
Where this record came from and when it was last checked.
- Reference
- Meta-Learning Fast Weight Language Models
- Last updated
- 25 May 2026
What the numbers mean
Where it came from
Transformer-XL + FWL was published by Google Research, in United States of America, in December 2022. industry is the category the publisher falls under.
It works in Language, and is recorded as doing language modeling/generation.
Its weights were never published, so it can only be reached through its provider. No graphics card changes that.
What went into building it
It was trained on about 103,000,000 tokens of text.
Answers
Transformer-XL + FWL — common questions
Is Transformer-XL + FWL open source?
No. Transformer-XL + FWL has not had its weights published, so it exists only as a service controlled by its owner.
How many parameters does Transformer-XL + FWL have?
Transformer-XL + FWL has 257M parameters. "For Transformer-XL, we use the large model (257M 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 Transformer-XL + FWL?
Transformer-XL + FWL was published by Google Research, based in United States of America, categorised as industry.
When was Transformer-XL + FWL released?
Transformer-XL + FWL was published in December 2022. 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 Transformer-XL + FWL used for?
Transformer-XL + FWL works in Language, and is recorded as handling language modeling/generation. These are the areas it was designed around; they describe intent rather than a hard boundary.
What GPU do I need to run Transformer-XL + FWL?
None. Transformer-XL + FWL 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.