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license: bsd-3-clause
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pipeline_tag: tabular-classification
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---
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# TabICL: A Tabular Foundation Model for In-Context Learning on Large Data
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TabICL is
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but is pre-trained on much larger datasets (up to 60K samples) and can handle even larger datasets
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thanks to its memory-efficient inference.
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If you use TabICL for research purposes,
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please cite our **[paper](https://arxiv.org/abs/2502.05564)
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---
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license: bsd-3-clause
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pipeline_tag: tabular-classification
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library_name: tabicl
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# TabICL: A Tabular Foundation Model for In-Context Learning on Large Data
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TabICL is a scalable tabular foundation model designed for classification tasks. Pre-trained on synthetic datasets with up to 60K samples, it can handle even larger datasets
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thanks to its memory-efficient inference.
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## Installation
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```bash
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pip install tabicl
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```
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The source code is available at [GitHub - soda-inria/tabicl](https://github.com/soda-inria/tabicl).
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## Citation
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If you use TabICL for research purposes,
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please cite our **[paper](https://arxiv.org/abs/2502.05564)**:
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```bibtex
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@article{qu2025tabicl,
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title={TabICL: A Tabular Foundation Model for In-Context Learning on Large Data},
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author={Qu, Jingang and Holzm{\"u}ller, David and Varoquaux, Ga{\"e}l and Morvan, Marine Le},
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journal={arXiv preprint arXiv:2502.05564},
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year={2025}
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}
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```
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