Update app.py

app.py

@@ -1,9 +1,23 @@
 import gradio as gr
-
+import torch
 from datasets import load_dataset
 
-dataset = load_dataset("zeroshot/twitter-financial-news-sentiment")
-dataset
+dataset = load_dataset("zeroshot/twitter-financial-news-sentiment", )
+
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
+
+model = AutoModelForSequenceClassification.from_pretrained("bert-base-uncased")
+tokenizer = AutoTokenizer.from_pretrained("bert-base-uncased")
+
+def sentiment_score(review):
+  tokens = tokenizer.encode(review, return_tensors='pt')
+  result = model(tokens)
+  return int(torch.argmax(result.logits))
+
+dataset['sentiment'] = dataset['text'].apply(lambda x: sentiment_score(x[:512]))
+
+print(dataset[:10])
+
 """
 categories = ('Car in good condition','Damaged Car')