Update app.py

app.py

@@ -5,14 +5,14 @@ from transformers import RobertaTokenizer, RobertaForSequenceClassification
 # Loading the pre-trained models and tokenizers from Hugging Face Hub
 sentiment_model = RobertaForSequenceClassification.from_pretrained("yestechies/fine_tuned_roberta_weighted")
 sentiment_tokenizer = RobertaTokenizer.from_pretrained("yestechies/fine_tuned_roberta_weighted")
-emotion_model = RobertaForSequenceClassification.from_pretrained("yestechies/emotion_model")
-emotion_tokenizer = RobertaTokenizer.from_pretrained("yestechies/emotion_model")
-intention_model = RobertaForSequenceClassification.from_pretrained("yestechies/intention_model")
-intention_tokenizer = RobertaTokenizer.from_pretrained("yestechies/intention_model")
+#emotion_model = RobertaForSequenceClassification.from_pretrained("yestechies/emotion_model")
+#emotion_tokenizer = RobertaTokenizer.from_pretrained("yestechies/emotion_model")
+#intention_model = RobertaForSequenceClassification.from_pretrained("yestechies/intention_model")
+#intention_tokenizer = RobertaTokenizer.from_pretrained("yestechies/intention_model")
 
 sentiment_model.eval()
-emotion_model.eval()
-intention_model.eval()
+#emotion_model.eval()
+#intention_model.eval()
 
 def predict_label(text, model, tokenizer, id2label):
     inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True)