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README.md
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@@ -36,9 +36,6 @@ You can then use this pipeline to classify sequences into any of the class names
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sequence_to_classify = "one day I will see the world"
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candidate_labels = ['travel', 'cooking', 'dancing']
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classifier(sequence_to_classify, candidate_labels)
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#{'sequence': 'one day I will see the world',
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# 'labels': ['travel', 'dancing', 'cooking'],
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# 'scores': [0.9878318905830383, 0.01044005248695612, 0.001728130504488945]}
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```
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If more than one candidate label can be correct, pass `multi_class=True` to calculate each class independently:
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```python
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candidate_labels = ['travel', 'cooking', 'dancing', 'exploration']
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classifier(sequence_to_classify, candidate_labels, multi_class=True)
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#{'sequence': 'one day I will see the world',
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# 'labels': ['exploration', 'travel', 'dancing', 'cooking'],
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# 'scores': [0.9956096410751343,
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# 0.9929478764533997,
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# 0.21706733107566833,
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# 0.0005817742203362286]}
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```
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### Eval results
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sequence_to_classify = "one day I will see the world"
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candidate_labels = ['travel', 'cooking', 'dancing']
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classifier(sequence_to_classify, candidate_labels)
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```
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If more than one candidate label can be correct, pass `multi_class=True` to calculate each class independently:
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```python
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candidate_labels = ['travel', 'cooking', 'dancing', 'exploration']
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classifier(sequence_to_classify, candidate_labels, multi_class=True)
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```
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### Eval results
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