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A BERT embedding library for sentence semantic similarity measurement.

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This is a sentence similarity measurement library using the forward pass of the BERT (bert-base-uncased) model. The spatial distance is computed using the cosine value between 2 semantic embedding vectors in low dimensional space. These vectors can be extracted by unique words as well as the sentence as a whole.The library also provides a flexibility for choosing any other approximators for spatial distance measurement for semantic similarity measurement.References include the BERT paper(https://arxiv.org/abs/1810.04805),Google Research BERT (https://github.com/google-research/bert/)

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