diff --git a/surprisal/model.py b/surprisal/model.py
index 0a10d6a..0671a02 100644
--- a/surprisal/model.py
+++ b/surprisal/model.py
@@ -321,7 +321,22 @@ def surprise(
         mask_mask = torch.eye(n, n)[1:, :].repeat(b, 1).bool()
         ids_with_bos_token[mask_mask] = self.tokenizer.mask_token_id
 
-        import IPython
+        # below is from ckauf and neuranna?
+        # if "within_word_l2r" == PLL_metric:
+        #     """
+        #     Future tokens belonging to the same word as the target token are masked during token inference as well.
+        #     """
+        #     mask_indices = [
+        #         [mask_pos]
+        #         + [
+        #             j
+        #             for j in range(mask_pos + 1, effective_length + 2)
+        #             if word_ids[j] == word_ids[mask_pos]
+        #         ]
+        #         if word_ids[mask_pos] is not None
+        #         else [mask_pos]
+        #         for mask_pos in range(effective_length + 2)
+        #     ]
 
         raise NotImplementedError
 
diff --git a/test.py b/test.py
index c6fa57d..3ed2654 100644
--- a/test.py
+++ b/test.py
@@ -5,11 +5,12 @@
 
 import surprisal
 
-g = surprisal.AutoHuggingFaceModel.from_pretrained(model_id="gpt2")
-# b = surprisal.AutoHuggingFaceModel.from_pretrained(model_id="bert-base-uncased")
+# m = surprisal.AutoHuggingFaceModel.from_pretrained(model_id="gpt2")
+m = surprisal.AutoHuggingFaceModel.from_pretrained(model_id="bert-base-uncased")
 
 
 stims = [
+    "The hooligan wrecked my new car!",
     "I am a cat on the mat",
     # "The cat sat on the mat.",
     # "The cat sat on the pizza.",
@@ -20,7 +21,7 @@
     # "How likely is a spicy burrito?",
 ]
 
-surps = [*g.surprise(stims), *g.surprise(stims, use_bos_token=False)]
+surps = [*m.surprise(stims), *m.surprise(stims, use_bos_token=False)]
 
 
 f, a = plt.subplots()