documents = [['human', 'interface', 'computer'], ['survey', 'user',
    'computer', 'system', 'response', 'time'], ['eps', 'user', 'interface',
    'system'], ['system', 'human', 'system', 'eps'], ['user', 'response',
    'time'], ['trees'], ['graph', 'trees'], ['graph', 'minors', 'trees'], [
    'graph', 'minors', 'survey']]
model = gensim.models.Word2Vec(documents, min_count=1)
print(model.similar_by_vector(model['survey'], topn=1))
Matching words and vectors in gensim Word2Vec model