diff --git a/README.md b/README.md
index ec4d9b9..e943690 100644
--- a/README.md
+++ b/README.md
@@ -10,10 +10,10 @@ python word2vec-api --model path/to/the/model [--host host --port 1234]
 
 * Example calls
 ```
-curl http://127.0.0.1:5000/wor2vec/n_similarity?ws1=Sushi&ws1=Shop&ws2=Japanese&ws2=Restaurant  
-curl http://127.0.0.1:5000/wor2vec/similarity?w1=Sushi&w2=Japanese   
-curl http://127.0.0.1:5000/wor2vec/most_similar?positive=indian&positive=food[&negative=][&topn=]
-curl http://127.0.0.1:5000/wor2vec/model?word=restaurant
+curl http://127.0.0.1:5000/word2vec/n_similarity?ws1=Sushi&ws1=Shop&ws2=Japanese&ws2=Restaurant
+curl http://127.0.0.1:5000/word2vec/similarity?w1=Sushi&w2=Japanese
+curl http://127.0.0.1:5000/word2vec/most_similar?positive=indian&positive=food[&negative=][&topn=]
+curl http://127.0.0.1:5000/word2vec/model?word=restaurant
 ```
 
 Note: The "model" method returns a base64 encoding of the Word2Vec vector.
diff --git a/word2vec-api.py b/word2vec-api.py
index 66a60e6..6c2c4d7 100644
--- a/word2vec-api.py
+++ b/word2vec-api.py
@@ -11,7 +11,7 @@
 from gensim.models.word2vec import Word2Vec as w
 from gensim import utils, matutils
 from numpy import exp, dot, zeros, outer, random, dtype, get_include, float32 as REAL,\
-    uint32, seterr, array, uint8, vstack, argsort, fromstring, sqrt, newaxis, ndarray, empty, sum as np_sum
+     uint32, seterr, array, uint8, vstack, argsort, fromstring, sqrt, newaxis, ndarray, empty, sum as np_sum
 import argparse
 import base64
 import sys
@@ -20,6 +20,8 @@
 
 
 def filter_words(words):
+    if words is None:
+        return
     return [word for word in words if word in model.vocab]
 
 
@@ -94,7 +96,7 @@ def raiseError(error):
 
 if __name__ == '__main__':
     global model
-    
+
     #----------- Parsing Arguments ---------------
     p = argparse.ArgumentParser()
     p.add_argument("--model", help="Path to the trained model")
@@ -102,12 +104,12 @@ def raiseError(error):
     p.add_argument("--host", help="Host name (default: localhost)")
     p.add_argument("--port", help="Port (default: 5000)")
     args = p.parse_args()
-    
+
     model_path = args.model if args.model else "./model.bin.gz"
     binary = True if args.binary else False
     host = args.host if args.host else "localhost"
     port = int(args.port) if args.port else 5000
     if not args.model:
-	print "Usage: wor2vec-apy.py --model path/to/the/model [--host host --port 1234]"
+        print "Usage: word2vec-apy.py --model path/to/the/model [--host host --port 1234]"
     model = w.load_word2vec_format(model_path, binary=binary)
     app.run(host=host, port=port)