TabPFN and tabpfn-client
TabPFN is the core foundation model for tabular data, while tabpfn-client is its complementary API wrapper library that provides easier programmatic access to the same underlying model—they are designed to be used together.
About TabPFN
PriorLabs/TabPFN
⚡ TabPFN: Foundation Model for Tabular Data ⚡
Based on the README, here's a technical summary: Built on a pretrained transformer architecture trained exclusively on synthetic data, TabPFN performs in-context learning by processing entire training sets through the model at inference time rather than traditional parameter updates. It provides scikit-learn compatible classifiers and regressors optimized for GPU inference on tabular datasets under 100K samples and 2000 features, with the ecosystem offering SHAP-based interpretability, synthetic data generation, embedding extraction, and hyperparameter optimization extensions.
About tabpfn-client
PriorLabs/tabpfn-client
⚡ Easy API access to the tabular foundation model TabPFN ⚡
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