title: Python gensim create word2vec model from vectors (in ndarray)
body: <p>I have a ndarray with words and their corresponding vector (with the size of 100 per word).
  For example:</p>
  
  <pre><code>Computer 0.11 0.41 ... 0.56
  Ball     0.31 0.87 ... 0.32
  </code></pre>
  
  <p>And so on.</p>
  
  <p>I want to create a word2vec model from it:</p>
  
  <pre><code>model = load_from_ndarray(arr)
  </code></pre>
  
  <p>How can it be done? I saw </p>
  
  <blockquote>
    <p>KeyedVectors</p>
  </blockquote>
  
  <p>but it only takes file and not array</p>