title: Gensim FastText - KeyError: "word not in vocabulary"
body: <p>I was having trouble with the "most_similar" call in a FastText model, from my understanding, Fasttext should be able to obtain results for words that aren't in the vocabulary, but I'm getting a "Not in Vocabulary" error, even when prior to saving and loading, the call was perfectly fine.</p>
  
  <p>Here's the code from juypter.</p>
  
  <pre><code>import gensim as gensim
  
  model = gensim.models.FastText(my_sentences, size=100, window=5, min_count=3, workers=4, sg=1)
  model.wv.most_similar(positive=['iPhone 6'])
  </code></pre>
  
  <p>Returns</p>
  
  <pre><code>[('iPhone7', 0.942690372467041),
  ('iPhone7.', 0.9395840764045715),
  ('iPhone5s', 0.9379133582115173),
  ('iPhone6s', 0.9338586330413818),
  ('iPhone5S', 0.9335439801216125),
  ('iPhone5.', 0.9318809509277344),
  ('iPhone®', 0.9314558506011963),
  ('iPhone6', 0.9268479347229004),
  ('iPhone4s', 0.9223971366882324),
  ('iPhone5', 0.9212019443511963)]
  </code></pre>
  
  <p>So far so good, now I save the model.</p>
  
  <pre><code>model.wv.save_word2vec_format("example_fasttext.txt", binary=False)
  </code></pre>
  
  <p>Then load it up again:</p>
  
  <pre><code>from gensim.models import KeyedVectors
  new_model = KeyedVectors.load_word2vec_format('example_fasttext.txt', binary=False, limit=50000)
  </code></pre>
  
  <p>Then I do the exact most_similar call from the model I just loaded:</p>
  
  <pre><code>new_model.most_similar(positive=['iPhone 6'])
  </code></pre>
  
  <p>But results now are:</p>
  
  <pre><code>KeyError: "word 'iPhone 6' not in vocabulary"
  </code></pre>
  
  <p>Any idea what I did wrong?</p>