Update app.py

app.py

@@ -7,7 +7,7 @@ console = Console()
 dataset = load_dataset("zeroshot/twitter-financial-news-sentiment", )
 
 console.log( dataset['train'][:10] )
-"""
+
 from transformers import AutoModelForSequenceClassification, AutoTokenizer
 
 model = AutoModelForSequenceClassification.from_pretrained("bert-base-uncased")
@@ -18,9 +18,9 @@ def sentiment_score(review):
   result = model(tokens)
   return int(torch.argmax(result.logits))
 
-dataset['sentiment'] = dataset['text'].apply(lambda x: sentiment_score(x[:512]))
-
+dataset['sentiment'] = dataset['train']['text'].apply(lambda x: sentiment_score(x[:512]))
 
+"""
 
 categories = ('Car in good condition','Damaged Car')