Update README.md

README.md

@@ -31,8 +31,8 @@ You can use these models in your own applications by leveraging the Hugging Face
 from transformers import pipeline
 
 # Load the AudienceClassifier model
-audience_classifier = pipeline("sentiment-classification", model="Moritz-Pfeifer/CentralBankRoBERTa-sentiment-classifier")
+audience_classifier = pipeline("text-classification", model="Moritz-Pfeifer/CentralBankRoBERTa-sentiment-classifier")
 
 # Perform audience classification
 sentinemnt_result = audience_classifier("The early effects of our policy tightening are also becoming visible, especially in sectors like manufacturing and construction that are more sensitive to interest rate changes.")
-print("Sentiment Classification:", sentinemnt_result[0]['label'])
+print("Sentiment:", sentinemnt_result[0]['label'])