Update app.py

app.py

@@ -71,7 +71,7 @@ def compute(df_table):
     
     ax.scatter(x_train[:, 0], x_train[:, 1], c=y_train_index, cmap=cm_bright)
     
-    classifier = TabPFNClassifier(base_path=tabpfn_path, device='cpu')
+    classifier = TabPFNClassifier(base_path=tabpfn_path, device='cpu', N_ensemble_configurations=4)
     classifier.fit(x_train[:, 0:2], y_train)
     
     DecisionBoundaryDisplay.from_estimator(
@@ -80,7 +80,7 @@ def compute(df_table):
     plt.xlabel(headers[0])
     plt.ylabel(headers[1])
 
-    return "The plot visualizes a predictor based on only two features and for two classes. The tabular results below are based on the full dataset.", out_table, fig
+    return "The plot visualizes a predictor based on only two features and for two classes. The tabular results below are based on the full dataset.\nThis demo is running on a CPU only and with 4 ensemble members (32 in the paper).", out_table, fig
 
 
 def upload_file(file, remove_entries=10):