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