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.
Zero-shot Time Series Forecasting with TabPFN (work accepted at NeurIPS 2024 TRL and TSALM workshops)
Community extensions for TabPFN - the foundation model for tabular data. Built with TabPFN! 🤗
⚡ Easy API access to the tabular foundation model TabPFN ⚡
Zero-shot Time Series Forecasting with TabPFN (work accepted at NeurIPS 2024 TRL and TSALM workshops)
Code for the paper "Out-of-the-Box Tabular Foundation Models for Bayesian Optimization in Materials Discovery" (AI4Mat, NeurIPS 2026).
Community extensions for TabPFN - the foundation model for tabular data. Built with TabPFN! 🤗
Shared Python utilities used across the TabPFN ecosystem — data helpers, regression result handling, cost estimation, and optional telemetry.
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