diff --git a/plugins/accelerated-moe/src/fms_acceleration_moe/utils/checkpoint_utils.py b/plugins/accelerated-moe/src/fms_acceleration_moe/utils/checkpoint_utils.py
index 1f14bcfc..024fcc16 100644
--- a/plugins/accelerated-moe/src/fms_acceleration_moe/utils/checkpoint_utils.py
+++ b/plugins/accelerated-moe/src/fms_acceleration_moe/utils/checkpoint_utils.py
@@ -257,11 +257,11 @@ def patch_huggingface_fsdp2_load_full_state_dict():
     from fms_acceleration.model_patcher import patch_target_module
 
     patch_target_module(
-        "accelerate.utils.fsdp_utils.fsdp2_load_full_state_dict",
-        fsdp2_load_full_state_dict,
+        "accelerate.accelerator.fsdp2_prepare_model", fsdp2_prepare_model
     )
     patch_target_module(
-        "accelerate.utils.fsdp_utils.fsdp2_prepare_model", fsdp2_prepare_model
+        "accelerate.utils.fsdp_utils.fsdp2_load_full_state_dict",
+        fsdp2_load_full_state_dict,
     )
 
 
@@ -734,11 +734,8 @@ def fsdp2_load_full_state_dict(accelerator, model: torch.nn.Module, full_sd: dic
             or a VRAM spike can occur
         full_sd (`dict`): The full state dict to load, can only be on rank 0
     """
-    # Third Party
-    # pylint: disable=import-outside-toplevel
-    from accelerate.utils.fsdp_utils import get_parameters_from_modules
-
     # pylint: disable=import-outside-toplevel
+    # Third Party
     from torch.distributed.tensor import distribute_tensor
     import torch.distributed as dist
 
@@ -774,13 +771,6 @@ def _cast_and_contiguous(tensor, to_contiguous, dtype):
             tensor = tensor.contiguous()
         return tensor
 
-    ignored_params = {
-        p.detach()
-        # pylint: disable=undefined-variable
-        for p in get_parameters_from_modules(
-            accelerator.state.fsdp_plugin.ignored_modules, model, accelerator.device
-        )
-    }
     if accelerator.is_main_process:
         for (param_name, full_param), sharded_param in zip(
             full_sd.items(), meta_sharded_sd.values()
@@ -907,7 +897,6 @@ def fsdp2_prepare_model(accelerator, model: torch.nn.Module) -> torch.nn.Module:
         if param.__class__.__name__ == "Params4bit":
             model_has_params4bit = True
             break
-
     if fsdp2_plugin.cpu_ram_efficient_loading and not model_has_params4bit:
         # pylint: disable=undefined-variable
         non_persistent_buffer_fqns = get_non_persistent_buffers(