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recsys-checkpoints
kevin-bretz/recsys-checkpoints
recsys-checkpoints is a machine learning model from kevin-bretz. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for pytorch. The card lists the license as mit.
The best trained checkpoints from my Recommender Systems coursework at Leiden University. Code and full details are in the GitHub repository kevin-bretz/recommender-systems.
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Updated Jul 12, 2026
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.pt180 MB · 100%
At a glance
- Library
- pytorch
- License
- mit
- Access
- Public
- Created
- Jul 10, 2026
- Updated
- Jul 12, 2026
- SHA
- 92de828f
Model card
From the Hugging Face model README
Recommender Systems checkpoints
The best trained checkpoints from my Recommender Systems coursework at Leiden University. Code and full details are in the GitHub repository kevin-bretz/recommender-systems.
Files
| Path | Model | Notes |
|---|---|---|
tiger/rqvae_K256_L3.pt | TIGER residual quantiser | Turns each item into a short semantic id (K=256, L=3, the default configuration). |
tiger/transformer_dropout0.2.pt | TIGER generator | Generates the next item's semantic id token by token. Dropout 0.2 was the best setting in the ablation, reaching Recall@10 of 0.0352. |
sasrec/sasrec_best.pt | SASRec | Self attentive sequential recommender, default configuration. |
These are inference weights only, no dataset is included. See the GitHub repository for how to load them and which dataset each was trained on.
- Library
- pytorch
- License
- mit
- Created
- Jul 10, 2026
- Updated
- Jul 12, 2026