update

swift/llm/model/register.py

@@ -355,7 +355,6 @@ def get_matched_model_meta(model_id_or_path: str) -> Optional[ModelMeta]:
 
 
 def _get_arch_mapping():
-    from .register import MODEL_MAPPING
     res = {}
     for model_type, model_meta in MODEL_MAPPING.items():
         architectures = model_meta.architectures
@@ -372,7 +371,7 @@ def get_matched_model_types(architectures: Optional[List[str]]) -> List[str]:
     """Get possible model_type."""
     architectures = architectures or ['nulll']
     if architectures:
-        arch = architectures[0]
+        architectures = architectures[0]
     arch_mapping = _get_arch_mapping()
     return arch_mapping.get(architectures) or []
 
@@ -385,10 +384,10 @@ def _get_model_info(model_dir: str, model_type: Optional[str], quantization_conf
     torch_dtype = HfConfigFactory.get_torch_dtype(config_dict, quant_info)
     max_model_len = HfConfigFactory.get_max_model_len(config_dict)
     rope_scaling = HfConfigFactory.get_config_attr(config_dict, 'rope_scaling')
-    architectures = HfConfigFactory.get_config_attr(config, 'architectures')
+    architectures = HfConfigFactory.get_config_attr(config_dict, 'architectures')
 
     if model_type is None:
-        model_types = get_matched_model_types(architectures)  # config.json
+        model_types = get_matched_model_types(architectures)
         if len(model_types) > 1:
             raise ValueError('Please explicitly pass the model_type. For reference, '
                              f'the available model_types: {model_types}.')