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@@ -67,13 +67,10 @@ This emotion classifier has been trained on 89_754 examples split into train, va
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  Usage:
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  ```python
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- from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
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-
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- tokenizer = AutoTokenizer.from_pretrained('AdamCodd/distilbert-base-uncased-finetuned-emotion-balanced')
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- model = AutoModelForSequenceClassification.from_pretrained('AdamCodd/distilbert-base-uncased-finetuned-emotion-balanced')
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  # Create the pipeline
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- emotion_classifier = pipeline('text-classification', model=model, tokenizer=tokenizer)
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  # Now you can use the pipeline to classify emotions
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  result = emotion_classifier("We are delighted that you will be coming to visit us. It will be so nice to have you here.")
 
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  Usage:
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  ```python
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+ from transformers import pipeline
 
 
 
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  # Create the pipeline
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+ emotion_classifier = pipeline('text-classification', model='AdamCodd/distilbert-base-uncased-finetuned-emotion-balanced')
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  # Now you can use the pipeline to classify emotions
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  result = emotion_classifier("We are delighted that you will be coming to visit us. It will be so nice to have you here.")