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Update README.md

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@@ -9,19 +9,17 @@ license: mit
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  Takes two sentences as inputs (one previous and one current utterance of a dialog). The previous sentence can be an empty string if this is the first utterance of a speaker in a dialog. **Outputs one of 11 labels**:
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  ```python
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- [
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- (0, 'acknowledge')
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- (1, 'answer')
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- (2, 'backchannel')
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- (3, 'reply_yes')
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- (4, 'exclaim')
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- (5, 'say')
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- (6, 'reply_no')
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- (7, 'hold')
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- (8, 'ask')
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- (9, 'intent')
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- (10, 'ask_yes_no')
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- ]
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  ```
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  ## Example:
@@ -31,7 +29,7 @@ from simpletransformers.classification import (
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  ClassificationModel, ClassificationArgs
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  )
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- model = ClassificationModel("deberta", "diwank/dyda-deberta-pair")
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  convert_to_label = lambda n: [
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  ['acknowledge',
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  'answer',
 
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  Takes two sentences as inputs (one previous and one current utterance of a dialog). The previous sentence can be an empty string if this is the first utterance of a speaker in a dialog. **Outputs one of 11 labels**:
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  ```python
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+ (0, 'acknowledge')
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+ (1, 'answer')
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+ (2, 'backchannel')
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+ (3, 'reply_yes')
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+ (4, 'exclaim')
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+ (5, 'say')
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+ (6, 'reply_no')
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+ (7, 'hold')
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+ (8, 'ask')
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+ (9, 'intent')
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+ (10, 'ask_yes_no')
 
 
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  ```
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  ## Example:
 
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  ClassificationModel, ClassificationArgs
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  )
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+ model = ClassificationModel("deberta", "diwank/silicone-deberta-pair")
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  convert_to_label = lambda n: [
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  ['acknowledge',
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  'answer',