Support the case where the model can predict NER entities but doesn't in that case

dan/ocr/predict/attention.py

@@ -44,7 +44,8 @@ def compute_offsets_by_level(full_text: str, level: Level, text_list: List[str])
     """
     # offsets[idx] = number of characters between text_list[idx-1] and text_list[idx]
     offsets = [int(level != Level.Char)] * (len(text_list) - 1)
-    if level == Level.NER:
+    # Take entities into account if there are any
+    if level == Level.NER and text_list:
         # Start after the first entity
         cursor = len(text_list[0])
         for idx, split in enumerate(text_list[1:]):