title: How to combine two pre-trained Word2Vec models?
body: <p>I successfully followed deeplearning4j.org tutorial on Word2Vec, so I am able to load already trained model or train a new one based on some raw text (more specifically, I am using <code>GoogleNews-vectors-negative300</code> and <code>Emoji2Vec</code> pre-trained model). </p>
  
  <p>However, I would like to combine these two above models for the following reason: Having a sentence (for example, a comment from Instagram or Twitter, which consists of emoji), I want to identify the emoji in the sentence and then map it to the word it is related to. In order to do that, I was planning to iterate over all the words in the sentence and calculate the closeness (how near the emoji and the word are located in the vector space).</p>
  
  <p>I <a href="https://github.com/deeplearning4j/dl4j-examples/blob/master/dl4j-examples/src/main/java/org/deeplearning4j/examples/nlp/word2vec/Word2VecUptrainingExample.java" rel="nofollow noreferrer">found the code</a> how to uptrain the already existing model. However, it is mentioned that new words are not added in this case and only weights for the existing words will be updated based on a new text corpus. </p>
  
  <p>I would appreciate any help or ideas on the problem I have. Thanks in advance!</p>