Instructions to use nums-ai/causilo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Causilo
How to use nums-ai/causilo with Causilo:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Add technical report link and citation to model card
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by dooho00 - opened
README.md
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Causilo is a pretrained tabular foundation model from Nums AI Inc., supporting classification and regression through a scikit-learn interface.
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## Files
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- `classifier/config.json` and `classifier/model.safetensors`: classification model.
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- These points summarize the License; the full text controls.
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Licensor: Nums AI Inc. Contact: contact@nums.world.
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Causilo is a pretrained tabular foundation model from Nums AI Inc., supporting classification and regression through a scikit-learn interface.
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[Technical report](https://arxiv.org/abs/2609.22866)
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## Files
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- `classifier/config.json` and `classifier/model.safetensors`: classification model.
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- These points summarize the License; the full text controls.
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Licensor: Nums AI Inc. Contact: contact@nums.world.
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## Citation
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If you use Causilo in research, please cite:
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```bibtex
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@misc{cho2026causilotechnicalreport,
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title={Causilo Technical Report},
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author={Minyong Cho and Minho Jeong and Dooho Lee and Jinmo Lee and Jaemin Yoo},
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year={2026},
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eprint={2609.22866},
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archivePrefix={arXiv},
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primaryClass={cs.LG},
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url={https://arxiv.org/abs/2609.22866},
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}
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```
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