title: Gensim built-in model.load function and Python Pickle.load file
body: <p>I was trying to use Gensim to import GoogelNews-pretrained model on some English words (sampled 15 ones here only stored in a txt file with each per line, and there are no more context as corpus). Then I could use "model.most_similar()" to get their similar words/phrases for them. But actually the file loaded from Python-Pickle method couldn't be used for gensim-built-in <code>model.load()</code> and <code>model.most_similar()</code> function directly. </p>
  
  <p>how should I do to cluster the 15 English words (and more in the future), since I couldn't train and save and load a model  from the beginning?</p>
  
  <pre><code>import gensim
  from gensim.models import Word2Vec
  from gensim.models.keyedvectors import KeyedVectors
  
  GOOGLE_WORD2VEC_MODEL = '../GoogleNews-vectors-negative300.bin'
  
  GOOGLE_ENGLISH_WORD_PATH = '../testwords.txt'
  
  GOOGLE_WORD_FEATURE = '../word.google.vector'
  
  model = gensim.models.KeyedVectors.load_word2vec_format(GOOGLE_WORD2VEC_MODEL, binary=True) 
  
  word_vectors = {}
  
  #load 15 words as a test to word_vectors
  
  with open(GOOGLE_ENGLISH_WORD_PATH) as f:
      lines = f.readlines()
      for line in lines:
          line = line.strip('\n')
          if line:                
              word = line
              print(line)
              word_vectors[word]=None
  try:
      import cPickle
  except :
      import _pickle as cPickle
  
  def save_model(clf,modelpath): 
      with open(modelpath, 'wb') as f: 
          cPickle.dump(clf, f) 
  
  def load_model(modelpath): 
      try: 
          with open(modelpath, 'rb') as f: 
              rf = cPickle.load(f) 
              return rf 
      except Exception as e:        
          return None 
  
  for word in word_vectors:
      try:
          v= model[word]
          word_vectors[word] = v
      except:
          pass
  
  save_model(word_vectors,GOOGLE_WORD_FEATURE)
  
  words_set = load_model(GOOGLE_WORD_FEATURE)
  
  words_set.most_similar("knit", topn=3)
  </code></pre>
  
  <blockquote>
  <pre><code>---------------error message--------
  AttributeError                            Traceback (most recent call last)
  &lt;ipython-input-8-86c15e366696&gt; in &lt;module&gt;
  ----&gt; 1 words_set.most_similar("knit", topn=3)
  
  AttributeError: 'dict' object has no attribute 'most_similar'
  ---------------error message--------
  </code></pre>
  </blockquote>