Character-enriched word2vec
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
- 15 July 2016
- Authors
- Piotr Bojanowski, Edouard Grave, Armand Joulin, Tomas Mikolov
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.
- Training data
- tokens
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Why it is tracked
- Highly cited
- Record confidence
- Unknown
- Citations
- 10,744
Sources
Where this record came from and when it was last checked.
- Reference
- Enriching Word Vectors with Subword Information
- Last updated
- 25 May 2026
What the numbers mean
What this model is
Character-enriched word2vec 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 language modeling.
Because the weights are not available, none of the hardware figures elsewhere on this site apply to it.
How it was trained
The reason it appears in this catalogue at all is highly cited.
Answers
Character-enriched word2vec — common questions
What GPU do I need to run Character-enriched word2vec?
None. Character-enriched word2vec 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 Character-enriched word2vec open source?
The licensing for Character-enriched word2vec was never recorded in our source data. We treat unstated licensing as closed, because an unrecorded licence is not one to rely on.
How many parameters does Character-enriched word2vec have?
No parameter count has been published for Character-enriched word2vec, which is why no memory or speed figure appears on this page.
Who created Character-enriched word2vec?
Character-enriched word2vec was published by Facebook AI Research, based in United States of America, categorised as industry.
When was Character-enriched word2vec released?
Character-enriched word2vec 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 Character-enriched word2vec used for?
Character-enriched word2vec works in Language, and is recorded as handling language modeling. Models frequently carry more than one of each, and the tags describe purpose rather than capability limits.
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.