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Update README.md
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README.md
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@@ -61,7 +61,7 @@ tokenizer = AutoTokenizer.from_pretrained("eventdata-utd/ConfliBERT-cont-cased-2
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model = AutoModelForMaskedLM.from_pretrained("eventdata-utd/ConfliBERT-cont-cased-20news")
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# Example of usage for binary classification task
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text = "The
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input_ids = tokenizer.encode(text, return_tensors='pt')
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outputs = model(input_ids)
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model = AutoModelForMaskedLM.from_pretrained("eventdata-utd/ConfliBERT-cont-cased-20news")
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# Example of usage for binary classification task
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text = "The Prime Minister of Brunei asked for protestors to remain peaceful during the upcoming Independence Day holiday."
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input_ids = tokenizer.encode(text, return_tensors='pt')
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outputs = model(input_ids)
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