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@@ -31,7 +31,7 @@ usage:
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  ```
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  model = AutoModelForSequenceClassification.from_pretrained("premsa/political-bias-prediction-allsides-DeBERTa")
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- tokenizer = AutoTokenizer.from_pretrained(premsa/"premsa/political-bias-prediction-allsides-DeBERTa")
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  nlp = pipeline("text-classification", model=model, tokenizer=tokenizer)
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  print(nlp("the masses are controlled by media."))
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  ```
 
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  ```
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  model = AutoModelForSequenceClassification.from_pretrained("premsa/political-bias-prediction-allsides-DeBERTa")
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+ tokenizer = AutoTokenizer.from_pretrained("premsa/political-bias-prediction-allsides-DeBERTa")
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  nlp = pipeline("text-classification", model=model, tokenizer=tokenizer)
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  print(nlp("the masses are controlled by media."))
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  ```