fastText
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
- Facebook AI Research
- Organisation type
- Industry
- Country
- United States of America, France
- Published
- 6 July 2016
- Authors
- A Joulin, E Grave, P Bojanowski, T Mikolov
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Language
- Task
- Text classification
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.
- Training data
- tokens
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Record confidence
- Unknown
- Citations
- 5,009
Sources
Where this record came from and when it was last checked.
- Reference
- Bag of Tricks for Efficient Text Classification
- Last updated
- 25 May 2026
What the numbers mean
Where it came from
fastText was published by Facebook AI Research, in United States of America, in July 2016. industry is the category the publisher falls under.
It works in Language, and is recorded as doing text classification.
This is a closed model: the trained values stayed with whoever produced them, and there is no local version to run.
Answers
fastText — common questions
How many parameters does fastText have?
No parameter count has been published for fastText, which is why no memory or speed figure appears on this page.
Who created fastText?
fastText was published by Facebook AI Research, based in United States of America, categorised as industry.
When was fastText released?
fastText was published in July 2016. 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 fastText used for?
fastText works in Language, and is recorded as handling text classification. These are the areas it was designed around; they describe intent rather than a hard boundary.
What GPU do I need to run fastText?
None. fastText 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 fastText open source?
The licensing for fastText was never recorded in our source data. We treat unstated licensing as closed, because an unrecorded licence is not one to rely on.
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.