title: What is the meaning of "size" of word2vec vectors [gensim library]?
body: <p>Assume that we have 1000 words (A1, A2,..., A1000) in a dictionary. As fa as I understand, in words embedding or word2vec method, it aims to represent each word in the dictionary by a vector where each element represents the similarity of that word with the remaining words in the dictionary. Is it correct to say there should be 999 dimensions in each vector, or the size of each word2vec vector should be 999?</p>
  
  <p>But with Gensim Python, we can modify the value of "size" parameter for Word2vec, let's say size = 100 in this case. So what does "size=100" mean? If we extract the output vector of A1, denoted (x1,x2,...,x100), what do x1,x2,...,x100 represent in this case?</p>