Model card: badges linking GitHub, PyPI, report and license
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README.md
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# LightPFN
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LightPFN is a small tabular foundation model for classification: a 4,603,088-parameter in-context learner
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pretrained only on synthetic data. `fit` stores the training set as context and `predict_proba` answers in one
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forward pass, with no training on your data and no hyperparameters to tune. It runs on CPU, CUDA, ROCm and, through
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# LightPFN
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<p>
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<a href="https://github.com/GioOtto/LightPFN"><img alt="Code on GitHub" src="https://img.shields.io/badge/Code-GitHub-181717?style=for-the-badge&logo=github&logoColor=white" /></a>
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<a href="https://pypi.org/project/LightPFN/"><img alt="Package on PyPI" src="https://img.shields.io/pypi/v/lightpfn?style=for-the-badge&logo=pypi&logoColor=white&label=PyPI&color=3775A9" /></a>
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<a href="https://huggingface.co/ueuegio/LightPFN/blob/main/LightPFN_report.pdf"><img alt="Technical report (PDF)" src="https://img.shields.io/badge/Technical%20report-PDF-8B1A1A?style=for-the-badge&logo=adobeacrobatreader&logoColor=white" /></a>
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<a href="https://github.com/GioOtto/LightPFN/blob/main/LICENSE"><img alt="License Apache 2.0" src="https://img.shields.io/badge/License-Apache%202.0-2F855A?style=for-the-badge" /></a>
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</p>
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LightPFN is a small tabular foundation model for classification: a 4,603,088-parameter in-context learner
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pretrained only on synthetic data. `fit` stores the training set as context and `predict_proba` answers in one
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forward pass, with no training on your data and no hyperparameters to tune. It runs on CPU, CUDA, ROCm and, through
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