Update app.py

app.py

@@ -8,6 +8,7 @@ from transformers import pipeline, AutoTokenizer, AutoModel
 tokenizer = AutoTokenizer.from_pretrained("furquan/opt-1-3b-prompt-tuned-sentiment-analysis", trust_remote_code=True)
 model = AutoModel.from_pretrained("furquan/opt-1-3b-prompt-tuned-sentiment-analysis", trust_remote_code=True)
 
+
 title = "OPT-1.3B"
 description = "This demo uses meta's opt-1.3b Causal LM as base model that was prompt tuned on the Stanford Sentiment Treebank-5 way dataset to only output the sentiment of a given text."
 article = "<p style='text-align: center'><a href='https://arxiv.org/pdf/2104.08691.pdf' target='_blank'>The Power of Scale for Parameter-Efficient Prompt Tuning</a></p>"