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I am trying to create a Word2Vec model of the the Pub Med Central corpus using the Gensim library and want to limit the total number of word embeddings to around 1 billion.

I have searched high and low and am unable to find out a) How to count the total number of word-embeddings in a saved model, and b) how to limit the total number of embeddings when training the model (once I hit 1 billion, then stop).

Please forgive my simpleton questions.

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Alright, after digging around in methods available to my loaded Word2Vec model I believe the answer is len(model.wv.vectors)...

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