---
license: other
license_name: causilo-1.0
license_link: LICENSE
library_name: causilo
pipeline_tag: tabular-classification
---

# Causilo

<p align="center">
  <img src="assets/causilo-logo.png" alt="Causilo — Tabular Foundation Model" width="300">
</p>

Causilo is a pretrained tabular foundation model from Nums AI Inc., supporting classification and regression through a scikit-learn interface.

[Technical report](https://arxiv.org/abs/2609.22866)

## Files

- `classifier/config.json` and `classifier/model.safetensors`: classification model.
- `regressor/config.json` and `regressor/model.safetensors`: regression model.

## Installation

Python 3.10–3.12 and PyTorch 2.13+ are required.

```bash
pip install causilo
```

The first fit automatically downloads and caches the checkpoint.

```python
from causilo import CausiloClassifier, CausiloRegressor

classifier = CausiloClassifier()
classifier.fit(X_train, y_train)
probabilities = classifier.predict_proba(X_test)

regressor = CausiloRegressor()
regressor.fit(X_train, y_train)
predictions = regressor.predict(X_test)
```

See the [code repository](https://github.com/nums-ai/causilo) for usage and [benchmarks](https://github.com/nums-ai/causilo#benchmarks).

## Licenses

- Python source and wheel: Apache-2.0; see [the code repository](https://github.com/nums-ai/causilo).
- Model weights: [Causilo License v1.0](LICENSE).
- Non-commercial research, testing, evaluation, experimentation and modifications are permitted subject to the License. Institutional affiliation alone does not determine whether a use is non-commercial.
- Free research redistribution of original copies and Derivatives is permitted under Section 3 without prior Company permission, with the required license, notices and modification information.
- Commercial or production use of the Model, Derivatives or Outputs requires separate licenses, subject to the scholarly-communication permission in Section 2(c).
- Hosted, managed, API or SaaS services require separate licenses whether paid or free. Hosting downloadable files under Section 3 is permitted.
- These points summarize the License; the full text controls.

Licensor: Nums AI Inc. Contact: contact@nums.world.

## Citation

If you use Causilo in research, please cite:

```bibtex
@misc{cho2026causilotechnicalreport,
  title={Causilo Technical Report},
  author={Minyong Cho and Minho Jeong and Dooho Lee and Jinmo Lee and Jaemin Yoo},
  year={2026},
  eprint={2609.22866},
  archivePrefix={arXiv},
  primaryClass={cs.LG},
  url={https://arxiv.org/abs/2609.22866},
}
```