Prior Labs builds tabular foundation models for structured data. TabPFN is our pre-trained model that makes predictions via in-context learning — provide your training rows, run one forward pass, and you're done. No retraining, no tuning loops. Pretrained on billions of synthetic tasks, it handles classification, regression, and forecasting on messy tables.
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tabpfn-time-series tabpfn-time-series Public
Zero-shot Time Series Forecasting with TabPFN (work accepted at NeurIPS 2024 TRL and TSALM workshops)
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tabpfn-extensions tabpfn-extensions Public
Community extensions for TabPFN - the foundation model for tabular data. Built with TabPFN! 🤗
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tabpfn-client tabpfn-client Public
⚡ Easy API access to the tabular foundation model TabPFN ⚡
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Repositories
- tabpfn-extensions Public
Community extensions for TabPFN - the foundation model for tabular data. Built with TabPFN! 🤗
- tabpfn-time-series Public
Zero-shot Time Series Forecasting with TabPFN (work accepted at NeurIPS 2024 TRL and TSALM workshops)
- .github Public
- openml-python Public Forked from openml/openml-python
openml but with fixes to make the cache read-only
- tabpfn_common_utils Public
Shared Python utilities used across the TabPFN ecosystem — data helpers, regression result handling, cost estimation, and optional telemetry.
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