AdClickNet
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
- Organisation type
- Industry
- Country
- United States of America
- Published
- 24 August 2014
- Authors
- Xinran He, Junfeng Pan, Ou Jin, Tianbing Xu, Bo Liu, Tao Xu, Yanxin Shi, Antoine Atallah, Ralf Herbrich, Stuart Bowers, Joaquin Quiñonero Candela
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Recommendation
- Task
- Recommender system, Click-through rate prediction
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
- 944
Sources
Where this record came from and when it was last checked.
- Reference
- Practical Lessons from Predicting Clicks on Ads at Facebook
- Last updated
- 1 January 2026
What the numbers mean
What this model is
AdClickNet was published by Facebook, in the country recorded as United States of America, during August 2014. The category the publisher falls under is industry.
It works in the domain of Recommendation, and is recorded as performing the task of recommender system, Click-through rate prediction.
Its weights were never published, so it can only be reached through its provider. No graphics card changes that.
Answers
AdClickNet — common questions
AdClickNet— how many parameters does it have?
No parameter count has been published for it, which is why no memory or speed figure appears on this page.
AdClickNet— who created it?
It was published by Facebook, based in United States of America, an organisation categorised as industry.
AdClickNet— when was it released?
It was published in August 2014. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
AdClickNet— what is it used for?
It works in the domain of Recommendation, and is recorded as handling the task of recommender system, Click-through rate prediction. A model can carry several of each, so these are the areas it was built for rather than a limit on what it will attempt.
AdClickNet— 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.
AdClickNet— is it open source?
The licensing 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.