NVIDIA Releases Kumo Tabular: Open Tabular Foundation Models That Predict New Rows in a Single Forward Pass
NVIDIA released Kumo Tabular, open tabular models that predict new rows in one forward pass.
NVIDIA released Kumo Tabular, tabular foundation models in Small, Medium, and Large sizes from about 28 million to 215 million parameters. They classify or regress new rows in one forward pass from labeled context, with no per-dataset training or feature engineering. Weights ship under OpenMDW-1.1, which permits commercial use, and run through the Apache-2.0 structured-data-models library. NVIDIA reports a TabArena Elo of 1950 and 17x faster inference than LimiX-2 on one RTX 6000 Pro; training used only synthetic structural causal model tables.
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