Update README.md

README.md

@@ -22,9 +22,12 @@ This is a XLM-roBERTa-base model trained on ~198M tweets and finetuned for senti
 from transformers import pipeline
 model_path = "cardiffnlp/twitter-xlm-roberta-base-sentiment"
 sentiment_task = pipeline("sentiment-analysis", model=model_path, tokenizer=model_path)
-
 sentiment_task("T'estimo!")
 ```
+Output: 
+```
+[{'label': 'LABEL_2', 'score': 0.6600581407546997}]
+```
 
 ## Full classification example