PriorLabs/TabPFN

⚡ TabPFN: Foundation Model for Tabular Data ⚡

80
/ 100
Verified

This tool helps data professionals quickly analyze and make predictions from structured data, like spreadsheets or databases. You input your raw tabular data, and it outputs predictions for classification (categorizing data) or regression (forecasting numerical values). It's designed for data scientists, analysts, or researchers who need to build predictive models without extensive manual tuning.

5,846 stars. Used by 5 other packages. Actively maintained with 34 commits in the last 30 days. Available on PyPI.

Use this if you have a moderately sized tabular dataset (up to 100,000 rows and 2000 columns) and need accurate predictions quickly without complex model configuration or extensive data preprocessing.

Not ideal if you have very large datasets (hundreds of thousands of rows or more) or require deep control over model architecture and training for highly specialized tasks.

data-analysis predictive-modeling classification regression business-intelligence
Maintenance 20 / 25
Adoption 15 / 25
Maturity 25 / 25
Community 20 / 25

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Stars

5,846

Forks

586

Language

Python

License

Last pushed

Mar 11, 2026

Commits (30d)

34

Dependencies

14

Reverse dependents

5

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