Create app.py

app.py

@@ -0,0 +1,35 @@
+import pandas as pd
+
+from autogluon.tabular import TabularPredictor
+
+
+if __name__ == '__main__':
+    train_data = pd.read_csv('https://autogluon.s3.amazonaws.com/datasets/Inc/train.csv')
+    subsample_size = 5000  
+    if subsample_size is not None and subsample_size < len(train_data):
+        train_data = train_data.sample(n=subsample_size, random_state=0)
+    test_data = pd.read_csv('https://autogluon.s3.amazonaws.com/datasets/Inc/test.csv')
+
+    tabpfnmix_default = {
+        "model_path_classifier": "autogluon/tabpfn-mix-1.0-classifier",
+        "model_path_regressor": "autogluon/tabpfn-mix-1.0-regressor",
+        "n_ensembles": 1,
+        "max_epochs": 30,
+    }
+
+    hyperparameters = {
+        "TABPFNMIX": [
+            tabpfnmix_default,
+        ],
+    }
+
+    label = "class"
+
+    predictor = TabularPredictor(label=label)
+    predictor = predictor.fit(
+        train_data=train_data,
+        hyperparameters=hyperparameters,
+        verbosity=3,
+    )
+
+    predictor.leaderboard(test_data, display=True)