Update model.py

model.py

@@ -588,6 +588,42 @@ def _get_revolab_pretrained_model(
 
         return recognizer
 
+    elif repo_id == "Revolab/zipformer-scaled-up":
+        
+            real_repo = 'Revolab/malaysian-pruned_transducer_stateless7'
+    
+            encoder_model = _get_nn_model_filename(
+                repo_id=real_repo,
+                filename="encoder-epoch-13-avg-5.onnx",
+                subfolder="zipformer-scale-up-pretrained/export",
+            )
+            decoder_model = _get_nn_model_filename(
+                repo_id=real_repo,
+                filename="encoder-epoch-13-avg-5.onnx",
+                subfolder="zipformer-scale-up-pretrained/export",
+            )
+    
+            joiner_model = _get_nn_model_filename(
+                repo_id=real_repo,
+                filename="joiner-epoch-13-avg-5.onnx",
+                subfolder="zipformer-scale-up-pretrained/export",
+            )
+    
+            tokens = _get_token_filename(repo_id=real_repo, subfolder="zipformer-scale-up-pretrained/export/lang_bpe_500")
+    
+            recognizer = sherpa_onnx.OfflineRecognizer.from_transducer(
+                tokens=tokens,
+                encoder=encoder_model,
+                decoder=decoder_model,
+                joiner=joiner_model,
+                num_threads=2,
+                sample_rate=16000,
+                feature_dim=80,
+                decoding_method=decoding_method,
+            )
+    
+            return recognizer
+
 @lru_cache(maxsize=10)
 def _get_zrjin_cantonese_pre_trained_model(
     repo_id: str, decoding_method: str, num_active_paths: int