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Document TabFM runtime behavior

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@@ -46,6 +46,13 @@ Model choices include Logistic, Linear Regression, Ridge, Bayesian Ridge, Naive
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  TabFM is always represented in the leaderboard: it appears as skipped until **Run TabFM live** is enabled, then reports live metrics when the run completes.
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  Note: TabFM's weights use their own non-commercial license. Review the upstream model license before using this Space commercially.
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  Links:
 
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  TabFM is always represented in the leaderboard: it appears as skipped until **Run TabFM live** is enabled, then reports live metrics when the run completes.
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+ ## Operational notes
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+ - The Space is pinned to Python 3.11 because TabFM's upstream package requires Python >= 3.11 and downloads weights from Hugging Face Hub.
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+ - TabFM is loaded with the correct checkpoint for the selected task: `model_type="classification"` for classification and `model_type="regression"` for regression.
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+ - Uploaded CSV runs coerce numeric regression targets, drop invalid target rows, and sanitize TabFM feature inputs before fitting.
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+ - The first live TabFM run can take a couple of minutes on CPU Basic while the model dependency and weights are loaded; later runs are faster while the Space remains warm.
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  Note: TabFM's weights use their own non-commercial license. Review the upstream model license before using this Space commercially.
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  Links: