Visualise word2vec generated from gensim

Question

I have trained a doc2vec and corresponding word2vec on my own corpus using gensim. I want to visualise the word2vec using t-sne with the words. As in, each dot in the figure has

Answer 1

With the following, you can convert your model to a TSV and then use this page for visualization.

with open(self.word_tensors_TSV, 'bw') as file_vector, open(self.word_meta_TSV, 'bw') as file_metadata:
    for word in model.wv.vocab:
        file_metadata.write((word + '\n').encode('utf-8', errors='replace'))
        vector_row = '\t'.join(str(x) for x in model[word])
        file_vector.write((vector_row + '\n').encode('utf-8', errors='replace'))

:)