hot-fix redundant import funasr (#12277)

python/llm/src/ipex_llm/transformers/npu_model.py

@@ -93,6 +93,9 @@ def from_pretrained(cls, *args, **kwargs):
             warnings.warn("`torch_dtype` will be ignored, `torch.float` will be used")
             kwargs["torch_dtype"] = torch.float32
 
+        if hasattr(cls, "get_cls_model"):
+            cls.HF_Model = cls.get_cls_model()
+
         low_bit = kwargs.pop("load_in_low_bit", "sym_int4")
         qtype_map = {
             "sym_int4": "sym_int4_rtn",
@@ -574,15 +577,19 @@ class AutoModelForTokenClassification(_BaseAutoModelClass):
 
 
 class FunAsrAutoModel(_BaseAutoModelClass):
-    import funasr
-    HF_Model = funasr.AutoModel
 
     def __init__(self, *args, **kwargs):
         self.model = self.from_pretrained(*args, **kwargs)
 
     def __getattr__(self, name):
         return getattr(self.model, name)
 
+    @classmethod
+    def get_cls_model(cls):
+        import funasr
+        cls_model = funasr.AutoModel
+        return cls_model
+
     @classmethod
     def optimize_npu_model(cls, *args, **kwargs):
         from ipex_llm.transformers.npu_models.convert_mp import optimize_funasr