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I want to create a text file that is essentially a dictionary, with each word being paired with its vector representation through word2vec. I'm assuming the process would be to first train word2vec and then look-up each word from my list and find its representation (and then save it in a new text file)?

I'm new to word2vec and I don't know how to go about doing this. I've read from several of the main sites, and several of the questions on Stack, and haven't found a good tutorial yet.

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You see, you cannot actually create a word2vec vector having just one word since word2vec estimates word vectors using context. It is trying to estimate the probability of your word to appear given some other word(s).

Or, in case you meant that you have some trained model, and you want to display a vector for a particular word, you’d better see the documentation of the library you use.

In gensim, for instance, it looks like this:

In[1]: model['computer']

# raw numpy vector of a word Out[1]: array([-0.00449447, -0.00310097, 0.02421786, ...], dtype=float32)

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