How to find the closest word to a vector using word2vec

Question

I have just started using Word2vec and I was wondering how can we find the closest word to a vector suppose. I have this vector which is the average vector for a set of vectors

Answer 1

Don't forget to add empty array with negative words in most_similar function:

import numpy as np
model_word_vector = np.array( my_vector, dtype='f')
topn = 20;
most_similar_words = model.most_similar( [ model_word_vector ], [], topn)