fixed app.py

app.py

@@ -19,12 +19,9 @@ def load_model(opt):
     elif opt == 'twitter-roberta-base-sentiment':
         tokenizer = AutoTokenizer.from_pretrained("cardiffnlp/twitter-roberta-base-sentiment")
         model = AutoModelForSequenceClassification.from_pretrained("cardiffnlp/twitter-roberta-base-sentiment")
-    elif opt == 'distilRoberta-financial-sentiment'
+    elif opt == 'distilRoberta-financial-sentiment':
         tokenizer = AutoTokenizer.from_pretrained("mrm8488/distilroberta-finetuned-financial-news-sentiment-analysis")
         model = AutoModelForSequenceClassification.from_pretrained("mrm8488/distilroberta-finetuned-financial-news-sentiment-analysis")
-    elif opt == 'bert-base-multilingual-uncased-sentiment ':
-        tokenizer = AutoTokenizer.from_pretrained("nlptown/bert-base-multilingual-uncased-sentiment")
-        model = AutoModelForSequenceClassification.from_pretrained("nlptown/bert-base-multilingual-uncas
     
     elif not model and not tokenizer: 
         print("Model not loaded correctly. Try again!")