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Update README.md
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README.md
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@@ -15,7 +15,7 @@ Model built under a TSI-100905-2019-4 project, co-financed by Ministry of Econom
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# How to use it
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The model answer the following question: Is "phrase B"
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Please note that we're considering phrases instead of sentences. Therefore, we must take into account that the model doesn't expect to find punctuation marks or long pieces of text.
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Resulting probabilities correspond to classes:
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@@ -41,4 +41,4 @@ Code output is:
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```
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tensor([[0.1592, 0.8408]], grad_fn=<SoftmaxBackward>)
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```
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As the probability of 1 is 0.84, we can conclude from the previous example that "could be included" is paraphrase of "may be
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# How to use it
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The model answer the following question: Is "phrase B" a paraphrase of "phrase A".
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Please note that we're considering phrases instead of sentences. Therefore, we must take into account that the model doesn't expect to find punctuation marks or long pieces of text.
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Resulting probabilities correspond to classes:
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```
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tensor([[0.1592, 0.8408]], grad_fn=<SoftmaxBackward>)
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```
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As the probability of 1 is 0.84, we can conclude from the previous example that "could be included" is paraphrase of "may be addressed".
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