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Word embedding is the collective name for a set of language modeling and feature learning techniques in NLP where words are mapped to vectors of real numbers in a low dimensional space, relative to the vocabulary size.

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How can i get the vector of word using BERT?

I need to get word-vectors using BERT and got this function that i think it should be the one i need def get_bert_embed_matrix(sentences): device = torch.device("cuda:0" if torch.cuda.is_available …
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