diff --git a/gensim/models/wrappers/fasttext.py b/gensim/models/wrappers/fasttext.py
index 752e14eccb..8678b55d5c 100644
--- a/gensim/models/wrappers/fasttext.py
+++ b/gensim/models/wrappers/fasttext.py
@@ -278,6 +278,12 @@ def load(cls, *args, **kwargs):
         if hasattr(model.wv, 'syn0_all'):
             setattr(model.wv, 'syn0_ngrams', model.wv.syn0_all)
             delattr(model.wv, 'syn0_all')
+        setattr(model.wv, 'bucket', model.wv.syn0_ngrams.shape[0])
+        if not hasattr(model.wv, 'hash2index') and hasattr(model.wv, 'ngrams'):
+            model.wv.hash2index = {}
+            for i, ngram in enumerate(model.wv.ngrams):
+                ngram_hash = ft_hash(ngram) % model.wv.bucket
+                model.wv.hash2index[ngram_hash] = i
         return model
 
     @classmethod
diff --git a/gensim/test/test_fasttext_wrapper.py b/gensim/test/test_fasttext_wrapper.py
index bc995f8159..247d4a0ba7 100644
--- a/gensim/test/test_fasttext_wrapper.py
+++ b/gensim/test/test_fasttext_wrapper.py
@@ -143,16 +143,16 @@ def testLoadFastTextFormat(self):
         # vector for oov words are slightly different from original FastText due to discarding unused ngrams
         # obtained using a modified version of ./fasttext print-word-vectors lee_fasttext_new.bin
         expected_vec_oov = [
-            -0.23825,
-            -0.58482,
-            -0.22276,
-            -0.41215,
-            0.91015,
-            -1.6786,
-            -0.26724,
-            0.58818,
-            0.57828,
-            0.75801
+            -0.21929,
+            -0.53778,
+            -0.22463,
+            -0.41735,
+            0.71737,
+            -1.59758,
+            -0.24833,
+            0.62028,
+            0.53203,
+            0.77568
         ]
         self.assertTrue(numpy.allclose(model["rejection"], expected_vec_oov, atol=1e-4))
 
@@ -194,16 +194,16 @@ def testLoadFastTextNewFormat(self):
         # vector for oov words are slightly different from original FastText due to discarding unused ngrams
         # obtained using a modified version of ./fasttext print-word-vectors lee_fasttext_new.bin
         expected_vec_oov = [
-            -0.53378,
-            -0.19,
-            0.013482,
-            -0.86767,
-            -0.21684,
-            -0.89928,
-            0.45124,
-            0.18025,
-            -0.14128,
-            0.22508
+            -0.49111,
+            -0.13122,
+            -0.02109,
+            -0.88769,
+            -0.20105,
+            -0.91732,
+            0.47243,
+            0.19708,
+            -0.17856,
+            0.19815
         ]
         self.assertTrue(numpy.allclose(new_model["rejection"], expected_vec_oov, atol=1e-4))
 
@@ -296,8 +296,6 @@ def testLookup(self):
         # Out of vocab check
         self.assertFalse('nights' in self.test_model.wv.vocab)
         self.assertTrue(numpy.allclose(self.test_model['nights'], self.test_model[['nights']]))
-        # Word with no ngrams in model
-        self.assertRaises(KeyError, lambda: self.test_model['a!@'])
 
     def testContains(self):
         """Tests __contains__ for in-vocab and out-of-vocab words"""
@@ -307,20 +305,14 @@ def testContains(self):
         # Out of vocab check
         self.assertFalse('nights' in self.test_model.wv.vocab)
         self.assertTrue('nights' in self.test_model)
-        # Word with no ngrams in model
-        self.assertFalse('a!@' in self.test_model.wv.vocab)
-        self.assertFalse('a!@' in self.test_model)
 
     def testWmdistance(self):
         """Tests wmdistance for docs with in-vocab and out-of-vocab words"""
         doc = ['night', 'payment']
         oov_doc = ['nights', 'forests', 'payments']
-        ngrams_absent_doc = ['a!@', 'b#$']
 
         dist = self.test_model.wmdistance(doc, oov_doc)
         self.assertNotEqual(float('inf'), dist)
-        dist = self.test_model.wmdistance(doc, ngrams_absent_doc)
-        self.assertEqual(float('inf'), dist)
 
     def testDoesntMatch(self):
         """Tests doesnt_match for list of out-of-vocab words"""
@@ -363,8 +355,8 @@ def testPersistenceForOldVersions(self):
             1.19031894, 2.01627707, 1.98942184, -1.39095843, -0.65036952])
         self.assertTrue(numpy.allclose(loaded_model["the"], in_expected_vec, atol=1e-4))
         # out-of-vocab word
-        out_expected_vec = numpy.array([-1.34948218, -0.8686831, -1.51483142, -1.0164026, 0.56272298,
-            0.66228276, 1.06477463, 1.1355902, -0.80972326, -0.39845538])
+        out_expected_vec = numpy.array([-0.33959097, -0.21121596, -0.37212455, -0.25057459, 0.11222091,
+        0.17517674, 0.26949012, 0.29352987, -0.1930912, -0.09438948])
         self.assertTrue(numpy.allclose(loaded_model["random_word"], out_expected_vec, atol=1e-4))