add qwen-2.5-7B-PRM/ernie-rm (#4319)

fastdeploy/model_executor/models/qwen2.py

@@ -44,6 +44,12 @@ from fastdeploy.model_executor.models.model_base import (
     ModelForCasualLM,
     ModelRegistry,
 )
+from fastdeploy.model_executor.utils import (
+    WeightsMapper,
+    default_weight_loader,
+    process_weights_after_loading,
+    process_weights_before_loading,
+)
 
 
 class Qwen2MLP(nn.Layer):
@@ -316,6 +322,14 @@ class Qwen2ForCausalLM(ModelForCasualLM):
             prefix="lm_head",
         )
 
+        self.process_weights_before_loading_fn = process_weights_before_loading(
+            mapper=(
+                WeightsMapper(orig_to_new_prefix={"model.": "qwen2."})
+                if self.fd_config.model_config.model_format == "torch"
+                else None
+            ),
+        )
+
     @paddle.no_grad()
     def load_weights(self, weights_iterator) -> None:
         """
@@ -325,11 +339,6 @@ class Qwen2ForCausalLM(ModelForCasualLM):
             weights_iterator (Iterator): An iterator yielding (name, weight) pairs.
         """
 
-        from fastdeploy.model_executor.utils import (
-            default_weight_loader,
-            process_weights_after_loading,
-        )
-
         stacked_params_mapping = [
             # (param_name, shard_name, shard_id)
             ("qkv_proj", "q_proj", "q"),
@@ -344,10 +353,13 @@ class Qwen2ForCausalLM(ModelForCasualLM):
         params_dict = dict(self.named_parameters())
         process_weights_after_loading_fn = process_weights_after_loading(dict(self.named_sublayers()))
         for loaded_weight_name, loaded_weight in weights_iterator:
-            model_format = self.fd_config.model_config.model_format
-            # Because the prefix for Paddle is qwen2, and for Hugging Face it is model.
-            if model_format == "torch":
-                loaded_weight_name = loaded_weight_name.replace("model", "qwen2")
+            loaded_weight_name = (
+                self.process_weights_before_loading_fn(loaded_weight_name)
+                if getattr(self, "process_weights_before_loading_fn", None)
+                else loaded_weight_name
+            )
+            if loaded_weight_name is None:
+                continue
             for param_name, weight_name, shard_id in stacked_params_mapping:
                 if weight_name not in loaded_weight_name:
                     continue