Update README.md

README.md

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