{"categories":[{"label":"Software Development","url":"https://skillfed.io/packages/category/software-development/9"},{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/5"}],"enrichment":{"capability":"TabPFN is a foundation model for tabular data that provides pre-trained classifiers and regressors for rapid inference on structured datasets without requiring hyperparameter tuning.","skillfed_tags":["tabular-ml","foundation-model","gpu-accelerated"],"use_cases":["Rapid prototyping on tabular datasets when you need a strong baseline without manual hyperparameter search.","Binary and multiclass classification on structured data with minimal preprocessing or model selection overhead.","Regression tasks on tabular data where you want pre-trained representations without training from scratch.","Exploratory analysis where you want to quickly assess model performance before investing in tuning.","Scenarios where you have a GPU available and want to leverage foundation model capabilities on tables."],"what_it_does":"TabPFN is a pre-trained foundation model designed to make tabular machine learning faster by eliminating hyperparameter tuning. It provides TabPFNClassifier and TabPFNRegressor classes that follow scikit-learn conventions, so you can fit and predict on structured data with minimal setup. The model downloads weights from huggingface-hub on first use and runs inference via torch, supporting both GPU and CPU execution (though GPU is strongly recommended).\n\nThe package depends on torch, scikit-learn, pandas, numpy, scipy, einops, pydantic, joblib, tqdm, and lightgbm. It supports Python 3.10 through 3.14. By default it uses TabPFN-3 (non-commercial license), but you can instantiate earlier versions like TabPFN-2.6 or TabPFN-2 via ModelVersion constants. For production use, Prior Labs offers a commercial Enterprise Edition.","worth_installing":"Yes, with conditions. TabPFN is worth installing if you work with tabular data and have a GPU available, or can tolerate CPU-only inference on moderate datasets. The package is actively maintained with low install friction and genuine value for rapid prototyping. Verify the non-commercial license restrictions for TabPFN-3 (the default) if your use is commercial; if so, you'll need a commercial license or use TabPFN-2 weights (Apache 2.0 with attribution). The attribution requirement is substantial\u2014ensure compliance before distributing."},"id":"tabpfn","links":{"html":"https://skillfed.io/packages/tabpfn","md":"https://skillfed.io/packages/tabpfn.md","pypi":"https://pypi.org/project/tabpfn/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-13","license_spdx":null,"license_treatment":"unclear","name":"tabpfn","python_support":"supports_current","summary":"TabPFN: Foundation model for tabular data"},"popularity":{"monthly_downloads":302996,"position":7815,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"8.3.0"}