diff --git a/lime/lime_tabular.py b/lime/lime_tabular.py
index 880f3d391..706eaed83 100644
--- a/lime/lime_tabular.py
+++ b/lime/lime_tabular.py
@@ -359,6 +359,8 @@ def explain_instance(self,
         ).ravel()
 
         yss = predict_fn(inverse)
+        if not isinstance(yss, np.ndarray): #pytorch output
+            yss = yss.detach().numpy() 
 
         # for classification, the model needs to provide a list of tuples - classes
         # along with prediction probabilities
@@ -505,7 +507,6 @@ def __data_inverse(self,
         else:
             num_cols = data_row.shape[0]
             data = np.zeros((num_samples, num_cols))
-        categorical_features = range(num_cols)
         if self.discretizer is None:
             instance_sample = data_row
             scale = self.scaler.scale_