TabFM is an open-source foundation model from Google Research for zero-shot classification and regression on tabular data. It supports mixed numerical and categorical columns and requires no fine-tuning, making it ideal for developers and researchers working with structured datasets.
Tabfm is a Data science & ML workbench product. Enabling developers to perform zero-shot classification and regression on tabular data without fine-tuning. Tabfm is an open-source project aimed at machine learning developers and researchers. The project is open source (Apache-2.0). Tabfm is available on the web, the command line, and API, and it can be self-hosted.
It is developed by Google Research, and the product first shipped in 2026. The project is developed in the open on GitHub with 1.1k stars and 91 commits in the last 90 days. Among its 5 catalogued features are zero-shot inference, tabular data support, and classification.
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TabFM: Zero-shot tabular foundation model from Google Research verified by the PulseGate indexer
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