Update app.py

app.py

@@ -109,23 +109,14 @@ class _MM9:
     def _load(self):
         try:
             self._dev = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-            # Using a fallback model since the base64 decoded path might not exist
-            try:
-                _mp = base64.b64decode("ZW50cm9weTI1L3NlbnRpbWVudGFuYWx5c2lz").decode()
-                self._tok = BertTokenizer.from_pretrained(_mp)
-                self._mdl = BertForSequenceClassification.from_pretrained(_mp)
-            except:
-                # Fallback to a publicly available model
-                _mp = "nlptown/bert-base-multilingual-uncased-sentiment"
-                self._tok = BertTokenizer.from_pretrained(_mp)
-                self._mdl = BertForSequenceClassification.from_pretrained(_mp)
-            
+            _mp = base64.b64decode("ZW50cm9weTI1L3NlbnRpbWVudGFuYWx5c2lz").decode()
+            self._tok = BertTokenizer.from_pretrained(_mp)
+            self._mdl = BertForSequenceClassification.from_pretrained(_mp)
             self._mdl.to(self._dev)
             _log.info(f"Model loaded on {self._dev}")
         except Exception as e:
             _log.error(f"Model loading failed: {e}")
             raise
-
 class _TP8:
     @staticmethod
     @lru_cache(maxsize=_cfg._c5)