diff --git a/docs/conf.py b/docs/conf.py
index 9fbde20..d700f8d 100644
--- a/docs/conf.py
+++ b/docs/conf.py
@@ -29,7 +29,7 @@
 author = 'Dimo Angelov'
 
 # The full version, including alpha/beta/rc tags
-release = '1.0.18'
+release = '1.0.19'
 
 
 # -- General configuration ---------------------------------------------------
diff --git a/setup.py b/setup.py
index a21f8ce..06f046e 100644
--- a/setup.py
+++ b/setup.py
@@ -6,7 +6,7 @@
 setuptools.setup(
     name="top2vec",
     packages=["top2vec"],
-    version="1.0.18",
+    version="1.0.19",
     author="Dimo Angelov",
     author_email="dimo.angelov@gmail.com",
     description="Top2Vec learns jointly embedded topic, document and word vectors.",
diff --git a/top2vec/Top2Vec.py b/top2vec/Top2Vec.py
index 4c7d187..fcb8ba3 100644
--- a/top2vec/Top2Vec.py
+++ b/top2vec/Top2Vec.py
@@ -402,7 +402,7 @@ def save(self, file):
             self.document_index = None
 
         # serialize word index so that it can be saved
-        if self.word_indexed:
+        if self.words_indexed:
             temp = tempfile.NamedTemporaryFile(mode='w+b')
             self.word_index.save_index(temp.name)
             self.serialized_word_index = temp.read()
diff --git a/top2vec/__init__.py b/top2vec/__init__.py
index 98911c2..b119265 100644
--- a/top2vec/__init__.py
+++ b/top2vec/__init__.py
@@ -1,3 +1,3 @@
 from top2vec.Top2Vec import Top2Vec
 
-__version__ = '1.0.18'
+__version__ = '1.0.19'
diff --git a/top2vec/tests/test_top2vec.py b/top2vec/tests/test_top2vec.py
index 47d1698..601e1fb 100644
--- a/top2vec/tests/test_top2vec.py
+++ b/top2vec/tests/test_top2vec.py
@@ -2,6 +2,7 @@
 from top2vec import Top2Vec
 from sklearn.datasets import fetch_20newsgroups
 import numpy as np
+import tempfile
 
 # get 20 newsgroups data
 newsgroups_train = fetch_20newsgroups(subset='all', remove=('headers', 'footers', 'quotes'))
@@ -457,3 +458,11 @@ def test_similar_words_index(top2vec_model):
 
     # check that words are returned in decreasing order
     assert all(word_scores[i] >= word_scores[i + 1] for i in range(len(word_scores) - 1))
+
+
+@pytest.mark.parametrize('top2vec_model', models)
+def test_similar_words_index(top2vec_model):
+    temp = tempfile.NamedTemporaryFile(mode='w+b')
+    top2vec_model.save(temp.name)
+    Top2Vec.load(temp.name)
+    temp.close()