Unrecorded-weight models from University of Toronto
12
Models
1 organisations
—
Open weights
0 open, 0 closed
2
Frontier
By Epoch's flag
140M
Largest traceable
Deep Autoencoders
2006–2017
Span
3 with a traceable size
Organisation
Country
Records
12| Model | Organisation | Released | Parameters | Weights |
|---|---|---|---|---|
| Prototypical networks | University of Toronto | 2017-03 | — | Not recorded |
| SC-NLM | University of Toronto | 2014-11 | — | Not recorded |
| PreTrans-3L-250H | University of Toronto | 2013-03 | 43M * | Not recorded |
| Bayesian automated hyperparameter tuning | University of Toronto | 2012-12 | — | Not recorded |
| AlexNet | University of Toronto | 2012-09 | 60M | Not recorded |
| Deep Autoencoders | University of Toronto | 2011-04 | 140M | Not recorded |
| ReLU (LFW) | University of Toronto | 2010-06 | — | Not recorded |
| ReLU (NORB) | University of Toronto | 2010-06 | 16M * | Not recorded |
| RBM Image Classifier | University of Toronto | 2009-04 | 80M * | Not recorded |
| HLBL | University of Toronto | 2008-12 | 2M | Not recorded |
| Deep Belief Nets | University of Toronto | 2006-07 | 2M * | Not recorded |
| Dimensionality Reduction | University of Toronto | 2006-07 | 4M * | Not recorded |
An asterisk marks a parameter figure the source does not consider traceable to the people who built the model. That judgement is the source’s and it has false negatives: Kimi K3 is marked speculative at 2.8T while Moonshot’s own model card states the figure. Why that distinction carries the whole exhibit.
Counts are of models Epoch AI records as notable, not of every model released. The most recent month is always incomplete, because a model enters the dataset when it is reviewed rather than when it ships.
Epoch AI, 'Data on AI Models'. Published online at epoch.ai. Retrieved from 'https://epoch.ai/data/ai-models-documentation' Used under CC BY 4.0.