title: How to speed up Gensim Word2vec model load time?
body: <p>I'm building a chatbot so I need to vectorize the user's input using Word2Vec. </p>
  
  <p>I'm using a pre-trained model with 3 million words by Google (GoogleNews-vectors-negative300).</p>
  
  <p>So I load the model using Gensim:</p>
  
  <pre><code>import gensim
  model = gensim.models.KeyedVectors.load_word2vec_format('GoogleNews-vectors-negative300.bin', binary=True)
  </code></pre>
  
  <p>The problem is that it takes about 2 minutes to load the model. I can't let the user wait that long.</p>
  
  <p>So what can I do to speed up the load time?</p>
  
  <p>I thought about putting each of the 3 million words and their corresponding vector into a MongoDB database. That would certainly speed things up but intuition tells me it's not a good idea.</p>