Maximum Entropy Models for machine translation
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
- University of Southern California,RWTH Aachen University
- Organisation type
- Academia,Academia
- Country
- United States of America, Germany
- Published
- 6 July 2002
- Authors
- Franz Josef Och and Hermann Ney
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Language
- Task
- Translation
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
- 58,073 tokens
[WORDS] Table 1
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Citations
- 1,413
Sources
Where this record came from and when it was last checked.
- Reference
- Discriminative Training and Maximum Entropy Models for Statistical Machine Translation
- Last updated
- 28 November 2025
What the numbers mean
About this model
Maximum Entropy Models for machine translation was published by University of Southern California,RWTH Aachen University, in the country recorded as United States of America, during July 2002. The publishing organisation is categorised as academia,Academia.
It works in the domain of Language, and is recorded as performing the task of translation.
Its weights were never published, so it can only be reached through its provider. No graphics card changes that.
How it was trained
Training consumed a corpus of around 58,073 tokens of text.
Answers
Maximum Entropy Models for machine translation — common questions
Maximum Entropy Models for machine translation— 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.
Maximum Entropy Models for machine translation— who created it?
It was published by University of Southern California,RWTH Aachen University, based in United States of America, an organisation categorised as academia,Academia.
Maximum Entropy Models for machine translation— when was it released?
It was published in July 2002. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
Maximum Entropy Models for machine translation— what is it used for?
It works in the domain of Language, and is recorded as handling the task of translation. Models frequently carry more than one of each, and the tags describe purpose rather than capability limits.
Maximum Entropy Models for machine translation— 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.
Maximum Entropy Models for machine translation— 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.