diff --git a/README.md b/README.md
index f2137a21..49d0211f 100644
--- a/README.md
+++ b/README.md
@@ -99,7 +99,7 @@ from pytorch_pretrained_bert import BertTokenizer, BertModel, BertForMaskedLM
 tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')
 
 # Tokenized input
-tokenized_text = "Who was Jim Henson ? Jim Henson was a puppeteer"
+text = "Who was Jim Henson ? Jim Henson was a puppeteer"
 tokenized_text = tokenizer.tokenize(text)
 
 # Mask a token that we will try to predict back with `BertForMaskedLM`
diff --git a/pytorch_pretrained_bert/tokenization.py b/pytorch_pretrained_bert/tokenization.py
index fab7b004..5c9369eb 100644
--- a/pytorch_pretrained_bert/tokenization.py
+++ b/pytorch_pretrained_bert/tokenization.py
@@ -65,7 +65,7 @@ def load_vocab(vocab_file):
     """Loads a vocabulary file into a dictionary."""
     vocab = collections.OrderedDict()
     index = 0
-    with open(vocab_file, "r") as reader:
+    with open(vocab_file, "r", encoding="utf8") as reader:
         while True:
             token = convert_to_unicode(reader.readline())
             if not token: