Update README.md

README.md

@@ -33,9 +33,9 @@ model = AutoModelForSequenceClassification.from_pretrained('NLP-LTU/bertweet-lar
 tokenizer = AutoTokenizer.from_pretrained('NLP-LTU/bertweet-large-sexism-detector') 
 classifier = pipeline("text-classification", model=model, tokenizer=tokenizer)
 prediction=classifier("Every woman wants to be a model. It's codeword for 'I get everything for free and people want me' ")
-label_pred = 'not sexist' if prediction == 0 else 'sexist' 
+# label_pred = 'not sexist' if prediction == 0 else 'sexist' 
 
-print(label_pred)
+print(prediction)
 ```
 our system rank 10 out of 84 teams, and our results on the test set was:
 ```