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app.py

@@ -66,9 +66,9 @@ def sentiment_analysis(
         return e_x / e_x.sum(axis=0)
 
     def analyze_text(text):
-        model_path = f"{dirname(__file__)}/{tokenizer_name_or_path}/"
+        model_path = f"{dirname(__file__)}/{model_name_or_path}/"
         print(f"Loading model from {model_path}")
-        tokenizer_path = f"{dirname(__file__)}/{model_name_or_path}/"
+        tokenizer_path = f"{dirname(__file__)}/{tokenizer_name_or_path}/"
         print(f"Loading tokenizer from {tokenizer_path}")
         tokenizer = AutoTokenizer.from_pretrained(tokenizer_path)
         model = AutoModelForSequenceClassification.from_pretrained(model_path)