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Update README.md

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@@ -20,12 +20,12 @@ Given two sentences (a premise and a hypothesis), the model outputs the logits o
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  You can test the model using the HuggingFace model widget on the side:
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  - Input two sentences (premise and hypothesis) one after the other.
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- - The model returns the probabilities of 3 labels: entailment, neutral and contradiction respectively.
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- To use the model locally:
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  ```
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- import torch
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- device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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  from transformers import AutoTokenizer, AutoModelForSequenceClassification
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  You can test the model using the HuggingFace model widget on the side:
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  - Input two sentences (premise and hypothesis) one after the other.
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+ - The model returns the probabilities of 3 labels: entailment(LABEL:0), neutral(LABEL:1) and contradiction(LABEL:2) respectively.
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+ To use the model locally on your machine:
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  ```
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+ # import torch
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+ # device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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  from transformers import AutoTokenizer, AutoModelForSequenceClassification
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