diff --git a/modules/sdnq/__init__.py b/modules/sdnq/__init__.py
index 6eb2e3553..bca210c1b 100644
--- a/modules/sdnq/__init__.py
+++ b/modules/sdnq/__init__.py
@@ -245,15 +245,6 @@ def apply_sdnq_to_module(model, weights_dtype="int8", torch_dtype=None, group_si
     return model
 
 
-class SDNQParameter(torch.nn.Parameter):
-    def __new__(cls, data=None, requires_grad=False):
-        return super().__new__(cls, data, requires_grad)
-
-    def __init__(self, data=None, requires_grad=False): # pylint: disable=unused-argument
-        self.original_shape = data.shape
-        super().__init__()
-
-
 class SDNQQuantizer(DiffusersQuantizer):
     r"""
     Diffusers Quantizer for SDNQ
@@ -342,7 +333,7 @@ class SDNQQuantizer(DiffusersQuantizer):
             param_value = param_value.to(target_device, non_blocking=self.quantization_config.non_blocking).to(dtype=torch.float32)
 
         layer, _ = get_module_from_name(model, param_name)
-        layer.weight = SDNQParameter(param_value, requires_grad=False)
+        layer.weight = torch.nn.Parameter(param_value, requires_grad=False)
         layer = sdnq_quantize_layer(
             layer,
             weights_dtype=weights_dtype,
diff --git a/pipelines/flux/flux_lora.py b/pipelines/flux/flux_lora.py
index 50f138df5..d7c80dc81 100644
--- a/pipelines/flux/flux_lora.py
+++ b/pipelines/flux/flux_lora.py
@@ -4,20 +4,24 @@ def calculate_module_shape(model, base_module=None, base_weight_param_name=None)
             return weight.quant_state.shape
         elif weight.__class__.__name__ == "GGUFParameter":
             return weight.quant_shape
-        elif weight.__class__.__name__ == "SDNQParameter":
-            return weight.original_shape
         else:
             return weight.shape
 
     if base_module is not None:
-        return _get_weight_shape(base_module.weight)
+        if hasattr(base_module, "sdnq_dequantizer"):
+            return base_module.sdnq_dequantizer.original_shape
+        else:
+            return _get_weight_shape(base_module.weight)
     elif base_weight_param_name is not None:
         from diffusers.utils import get_submodule_by_name
         if not base_weight_param_name.endswith(".weight"):
             raise ValueError(f"Invalid `base_weight_param_name` passed as it does not end with '.weight' {base_weight_param_name=}.")
         module_path = base_weight_param_name.rsplit(".weight", 1)[0]
         submodule = get_submodule_by_name(model, module_path)
-        return _get_weight_shape(submodule.weight)
+        if hasattr(submodule, "sdnq_dequantizer"):
+            return submodule.sdnq_dequantizer.original_shape
+        else:
+            return _get_weight_shape(submodule.weight)
 
     raise ValueError("Either `base_module` or `base_weight_param_name` must be provided.")