title: Gensim: KeyError: "word not in vocabulary"
body: <p>I have a trained Word2vec model using Python's Gensim Library. I have a tokenized list as below. The vocab size is 34 but I am just giving few out of 34:</p>
  
  <pre><code>b = ['let',
   'know',
   'buy',
   'someth',
   'featur',
   'mashabl',
   'might',
   'earn',
   'affili',
   'commiss',
   'fifti',
   'year',
   'ago',
   'graduat',
   '21yearold',
   'dustin',
   'hoffman',
   'pull',
   'asid',
   'given',
   'one',
   'piec',
   'unsolicit',
   'advic',
   'percent',
   'buy']
  </code></pre>
  
  <p><strong>Model</strong></p>
  
  <pre><code>model = gensim.models.Word2Vec(b,min_count=1,size=32)
  print(model) 
  ### prints: Word2Vec(vocab=34, size=32, alpha=0.025) ####
  </code></pre>
  
  <p>if I try to get the similarity score by doing <code>model['buy']</code> of one the words in the list, I get the </p>
  
  <blockquote>
    <p>KeyError: "word 'buy' not in vocabulary"</p>
  </blockquote>
  
  <p>Can you guys suggest me what I am doing wrong and what are the ways to check the model which can be further used to train PCA or t-sne in order to visualize similar words forming a topic? Thank you. </p>