title: Gensim word2vec augment or merge pre-trained vectors
body: <p>I am loading pre-trained vectors from a binary file generated from the word2vec C code with something like:</p>
  
  <pre><code>model_1 = Word2Vec.load_word2vec_format('vectors.bin', binary=True)
  </code></pre>
  
  <p>I am using those vectors to generate vector representations of sentences that contain words that may not have already existing vectors in <code>vectors.bin</code>. For example, if <code>vectors.bin</code> has no associated vector for the word "yogurt", and I try</p>
  
  <pre><code>yogurt_vector = model_1['yogurt']
  </code></pre>
  
  <p>I get <code>KeyError: 'yogurt'</code>, which makes good sense. What I want is to be able to take the sentence words that do not have corresponding vectors and add representations for them to <code>model_1</code>. I am aware from <a href="https://stackoverflow.com/questions/22121028/update-gensim-word2vec-model">this post</a> that you cannot continue to train the C vectors. Is there then a way to train a new model, say <code>model_2</code>, for the words with no vectors and merge <code>model_2</code> with <code>model_1</code>?</p>
  
  <p>Alternatively, is there a way to test if the model contains a word before I actually try to retrieve it, so that I can at least avoid the KeyError?</p>