mini-GPT-2+Active-AdamW
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
- HEC Montreal
- Organisation type
- Academia
- Country
- Canada
- Published
- 24 January 2023
- Authors
- Davood Wadi, Marc Fredette, Sylvain Senecal
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
- Epochs
- 200
The training run
What it physically took to train: which chips, how many, for how long, and what that drew from the wall.
- Training hardware
- NVIDIA V100,NVIDIA P100
- Chips used
- 1
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
- Confident
- Benchmark data
- mini-GPT-2+Active-AdamW
Sources
Where this record came from and when it was last checked.
- Reference
- Read the Signs Towards Invariance to Gradient Descent’s Hyperparameter Initialization
- Last updated
- 28 November 2025
What the numbers mean
What this model is
mini-GPT-2+Active-AdamW was published by HEC Montreal, in the country recorded as Canada, during January 2023. 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 weights were never published, so it can only be reached through its provider. No graphics card changes that.
Answers
mini-GPT-2+Active-AdamW — common questions
mini-GPT-2+Active-AdamW— 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.
mini-GPT-2+Active-AdamW— 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.
mini-GPT-2+Active-AdamW— is it open source?
No. Its weights have not been published, so it exists only as a service controlled by its owner.
mini-GPT-2+Active-AdamW— 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.
mini-GPT-2+Active-AdamW— who created it?
It was published by HEC Montreal, based in Canada, an organisation categorised as academia.
mini-GPT-2+Active-AdamW— when was it released?
It was published in January 2023. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
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.