Update app.py

app.py

@@ -3,7 +3,8 @@ import torch
 from datasets import load_dataset
 
 dataset = load_dataset("zeroshot/twitter-financial-news-sentiment", )
-
+print(dataset[:10])
+break
 from transformers import AutoModelForSequenceClassification, AutoTokenizer
 
 model = AutoModelForSequenceClassification.from_pretrained("bert-base-uncased")
@@ -16,7 +17,7 @@ def sentiment_score(review):
 
 dataset['sentiment'] = dataset['text'].apply(lambda x: sentiment_score(x[:512]))
 
-print(dataset[:10])
+
 
 """
 categories = ('Car in good condition','Damaged Car')