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README.md
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example_title: "Biased example 1"
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- text: "Christians should make clear that the perpetuation of objectionable vaccines and the lack of alternatives is a kind of coercion."
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example_title: "Biased example 2"
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- text: "
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example_title: "Non-Biased example 1"
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- text: "While emphasizing he’s not singling out either party, Cohen warned about the danger of normalizing white supremacist ideology."
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example_title: "Non-Biased example 2"
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@@ -32,7 +32,7 @@ tokenizer = AutoTokenizer.from_pretrained("dreji18/bias-detection-model", use_au
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model = TFAutoModelForSequenceClassification.from_pretrained("dreji18/bias-detection-model", use_auth_token=True)
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classifier = pipeline('text-classification', model=model, tokenizer=tokenizer) # cuda = 0,1 based on gpu availability
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classifier("
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```
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## Author
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example_title: "Biased example 1"
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- text: "Christians should make clear that the perpetuation of objectionable vaccines and the lack of alternatives is a kind of coercion."
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example_title: "Biased example 2"
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- text: "There have been a protest by a group of people"
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example_title: "Non-Biased example 1"
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- text: "While emphasizing he’s not singling out either party, Cohen warned about the danger of normalizing white supremacist ideology."
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example_title: "Non-Biased example 2"
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model = TFAutoModelForSequenceClassification.from_pretrained("dreji18/bias-detection-model", use_auth_token=True)
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classifier = pipeline('text-classification', model=model, tokenizer=tokenizer) # cuda = 0,1 based on gpu availability
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classifier("The irony, of course, is that the exhibit that invites people to throw trash at vacuuming Ivanka Trump lookalike reflects every stereotype feminists claim to stand against, oversexualizing Ivanka’s body and ignoring her hard work.")
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```
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## Author
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