diff --git a/ernie/__init__.py b/ernie/__init__.py
index 3344544..a484e73 100644
--- a/ernie/__init__.py
+++ b/ernie/__init__.py
@@ -5,7 +5,7 @@
 from tensorflow.python.client import device_lib
 import logging
 
-__version__ = '1.2307.0'
+__version__ = '1.2308.0'
 
 logging.getLogger().setLevel(logging.WARNING)
 logging.getLogger("transformers.tokenization_utils").setLevel(logging.ERROR)
diff --git a/ernie/ernie.py b/ernie/ernie.py
index e4a7923..eb801db 100644
--- a/ernie/ernie.py
+++ b/ernie/ernie.py
@@ -266,9 +266,17 @@ def _predict_batch(
                     add_special_tokens=True,
                     max_length=self._tokenizer.model_max_length,
                 )
+
+                input_ids = features['input_ids']
+                if 'token_type_ids' in features:
+                    token_type_ids = features['token_type_ids']
+                else:
+                    token_type_ids = [0] * len(input_ids)  # fill with zeros
+
                 input_ids, _, attention_mask = (
-                    features['input_ids'], features['token_type_ids'],
-                    features['attention_mask']
+                    input_ids,
+                    token_type_ids,
+                    features['attention_mask'],
                 )
 
                 input_ids = self._list_to_padded_array(features['input_ids'])
diff --git a/ernie/helper.py b/ernie/helper.py
index 754aaf9..52b9e06 100644
--- a/ernie/helper.py
+++ b/ernie/helper.py
@@ -15,17 +15,22 @@ def get_features(tokenizer, sentences, labels):
             add_special_tokens=True,
             max_length=tokenizer.model_max_length,
         )
-        input_ids, token_type_ids = (
-            inputs['input_ids'],
-            inputs['token_type_ids'],
-        )
+
+        input_ids = inputs['input_ids']
+        if 'token_type_ids' in inputs:
+            token_type_ids = inputs['token_type_ids']
+        else:
+            token_type_ids = [0] * len(input_ids)  # fill with zeros
+
         padding_length = tokenizer.model_max_length - len(input_ids)
 
         if tokenizer.padding_side == 'right':
             attention_mask = [1] * len(input_ids) + [0] * padding_length
             input_ids = input_ids + [tokenizer.pad_token_id] * padding_length
-            token_type_ids = token_type_ids + \
-                [tokenizer.pad_token_type_id] * padding_length
+            token_type_ids = (
+                token_type_ids + [tokenizer.pad_token_type_id] * padding_length
+            )
+
         else:
             attention_mask = [0] * padding_length + [1] * len(input_ids)
             input_ids = [tokenizer.pad_token_id] * padding_length + input_ids