diff --git a/pytorch_pretrained_bert/tokenization.py b/pytorch_pretrained_bert/tokenization.py
index 9cfb3d8ce9..9cb36a1b46 100644
--- a/pytorch_pretrained_bert/tokenization.py
+++ b/pytorch_pretrained_bert/tokenization.py
@@ -75,7 +75,8 @@ def whitespace_tokenize(text):
 class BertTokenizer(object):
     """Runs end-to-end tokenization: punctuation splitting + wordpiece"""
 
-    def __init__(self, vocab_file, do_lower_case=True, max_len=None):
+    def __init__(self, vocab_file, do_lower_case=True, max_len=None,
+                 never_split=("[UNK]", "[SEP]", "[PAD]", "[CLS]", "[MASK]")):
         if not os.path.isfile(vocab_file):
             raise ValueError(
                 "Can't find a vocabulary file at path '{}'. To load the vocabulary from a Google pretrained "
@@ -83,7 +84,8 @@ class BertTokenizer(object):
         self.vocab = load_vocab(vocab_file)
         self.ids_to_tokens = collections.OrderedDict(
             [(ids, tok) for tok, ids in self.vocab.items()])
-        self.basic_tokenizer = BasicTokenizer(do_lower_case=do_lower_case)
+        self.basic_tokenizer = BasicTokenizer(do_lower_case=do_lower_case,
+                                              never_split=never_split)
         self.wordpiece_tokenizer = WordpieceTokenizer(vocab=self.vocab)
         self.max_len = max_len if max_len is not None else int(1e12)
 
@@ -156,13 +158,16 @@ class BertTokenizer(object):
 class BasicTokenizer(object):
     """Runs basic tokenization (punctuation splitting, lower casing, etc.)."""
 
-    def __init__(self, do_lower_case=True):
+    def __init__(self,
+                 do_lower_case=True,
+                 never_split=("[UNK]", "[SEP]", "[PAD]", "[CLS]", "[MASK]")):
         """Constructs a BasicTokenizer.
 
         Args:
           do_lower_case: Whether to lower case the input.
         """
         self.do_lower_case = do_lower_case
+        self.never_split = never_split
 
     def tokenize(self, text):
         """Tokenizes a piece of text."""
@@ -198,6 +203,8 @@ class BasicTokenizer(object):
 
     def _run_split_on_punc(self, text):
         """Splits punctuation on a piece of text."""
+        if text in self.never_split:
+            return [text]
         chars = list(text)
         i = 0
         start_new_word = True