Transformer-XL + SIS
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
- INRIA
- Organisation type
- Academia
- Country
- France
- Published
- 3 May 2021
- Authors
- Sagar Verma, Jean-Christophe Pesquet
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
- Transformer-XL (257M)
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
- 246M
- Training data
- tokens
246M "Transformer-XL is a language model with 246 million parameters."
Training compute
The arithmetic performed to train the model, measured in floating-point operations. It is a measure of what the training run cost, not of how fast the finished model answers you.
- Training compute
- 3.8 × 10²⁰ FLOP
- How it was established
- Comparison with other models
base model training compute: 3.7832771e+20 FLOP
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
- Speculative
- Citations
- 15
- Benchmark data
- Transformer-XL + SIS
Sources
Where this record came from and when it was last checked.
- Reference
- Sparsifying Networks via Subdifferential Inclusion
- Last updated
- 1 December 2025
What the numbers mean
Where it came from
Transformer-XL + SIS was published by INRIA, in the country recorded as France, during May 2021. The publishing organisation is categorised as academia.
It works in the domain of Language, and is recorded as performing the task of language modeling.
Its starting point was an existing base model, Transformer-XL (257M). That is the usual way a specialised model is produced.
This is a closed model: the trained values stayed with whoever produced them, and there is no local version to run.
Training and provenance
Producing it required arithmetic totalling around 3.8 × 10²⁰ FLOP. That figure measures what producing the model cost, and has no bearing on how fast it answers.
Answers
Transformer-XL + SIS — common questions
Transformer-XL + SIS— is it open source?
No. Its weights have not been published, so it exists only as a service controlled by its owner.
Transformer-XL + SIS— how many parameters does it have?
It has a parameter count of 246M. 246M "Transformer-XL is a language model with 246 million 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.
Transformer-XL + SIS— who created it?
It was published by INRIA, based in France, an organisation categorised as academia.
Transformer-XL + SIS— when was it released?
It was published in May 2021. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
Transformer-XL + SIS— what is it used for?
It works in the domain of Language, and is recorded as handling the task of language modeling. Models frequently carry more than one of each, and the tags describe purpose rather than capability limits.
Transformer-XL + SIS— how much compute was used to train it?
Training consumed around 3.8 × 10²⁰ FLOP. That measures what producing the model cost and says nothing about how quickly it answers once trained — inference speed comes from memory bandwidth, not from the training budget.
Transformer-XL + SIS— 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.