Update load_model.py

load_model.py

@@ -8,13 +8,13 @@ load_dotenv()
 def load_model(model_name):
     try:
         # Load TensorFlow model from Hugging Face
-        model = TFBertForSequenceClassification.from_pretrained(model_name, use_auth_token=os.getenv('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'), from_tf=True)
+        model = TFBertForSequenceClassification.from_pretrained(model_name, use_auth_token=os.getenv('API_KEY'), from_tf=True)
     except OSError:
         raise ValueError("Model loading failed.")
     return model
 
 def load_tokenizer(model_name):
-    tokenizer = BertTokenizerFast.from_pretrained(model_name, use_auth_token=os.getenv('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'))
+    tokenizer = BertTokenizerFast.from_pretrained(model_name, use_auth_token=os.getenv('API_KEY'))
     return tokenizer
 
 def predict(text, model, tokenizer):
@@ -23,9 +23,9 @@ def predict(text, model, tokenizer):
     return outputs
 
 def main():
-    model_name = os.getenv('Erfan11/Neuracraft')
+    model_name = os.getenv('MODEL_PATH')
     if model_name is None:
-        raise ValueError("Erfan11/Neuracraft environment variable not set or is None")
+        raise ValueError("MODEL_PATH environment variable not set or is None")
 
     model = load_model(model_name)
     tokenizer = load_tokenizer(model_name)