diff --git a/MindIE/MindIE-Torch/built-in/foundation/stable_diffusion_xl/convert_lora_safetensors_to_diffusers.py b/MindIE/MindIE-Torch/built-in/foundation/stable_diffusion_xl/convert_lora_safetensors_to_diffusers.py
index 2f449cc28dac1c7f527b46acb4a62927ff5acc20..940bc0c89352e2ba3aab417a102065e0152b0526 100644
--- a/MindIE/MindIE-Torch/built-in/foundation/stable_diffusion_xl/convert_lora_safetensors_to_diffusers.py
+++ b/MindIE/MindIE-Torch/built-in/foundation/stable_diffusion_xl/convert_lora_safetensors_to_diffusers.py
@@ -20,6 +20,7 @@ import torch
 from safetensors.torch import load_file
 
 from diffusers import StableDiffusionXLPipeline
+from diffusers.models.lora import LoRACompatibleConv, LoRACompatibleLinear
 
 
 def convert(base_model_path, checkpoint_path, LORA_PREFIX_UNET, LORA_PREFIX_TEXT_ENCODER, alpha):
@@ -78,24 +79,17 @@ def convert(base_model_path, checkpoint_path, LORA_PREFIX_UNET, LORA_PREFIX_TEXT
             pair_keys.append(key.replace("lora_up", "lora_down"))
 
         # update weight
-        if len(state_dict[pair_keys[0]].shape) == 4:
-            weight_up = state_dict[pair_keys[0]].squeeze(3).squeeze(2).to(torch.float32)
-            weight_down = state_dict[pair_keys[1]].squeeze(3).squeeze(2).to(torch.float32)
-            try:
-                if len(curr_layer.weight.shape) == 2:
-                    curr_layer.weight.data += alpha * torch.mm(weight_up, weight_down) # for SD2.1
-                else:
-                    curr_layer.weight.data += alpha * torch.mm(weight_up, weight_down).unsqueeze(2).unsqueeze(3)
-            except Exception:
-                shape4failed += 1
-        else:
-            weight_up = state_dict[pair_keys[0]].to(torch.float32)
-            weight_down = state_dict[pair_keys[1]].to(torch.float32)
-            try:
-                curr_layer.weight.data += alpha * torch.mm(weight_up, weight_down)
-            except Exception:
-                shapeno4failed += 1
-
+        if isinstance(curr_layer, LoRACompatibleConv):
+            upmat = state_dict[pair_keys[0]].to(torch.float32).flatten(start_dim=1)
+            downmat = state_dict[pair_keys[1]].to(torch.float32).flatten(start_dim=1)
+            fusionupdown = torch.mm(upmat, downmat)
+            fusionupdown = fusionupdown.reshape(curr_layer.weight.data.shape)
+            curr_layer.weight.data += alpha * fusionupdown
+        elif isinstance(curr_layer,LoRACompatibleLinear):
+            upmat = state_dict[pair_keys[0]].to(torch.float32)[None, :]
+            downmat = state_dict[pair_keys[1]].to(torch.float32)[None, :]
+            fusion = torch.bmm(upmat, downmat)[0]
+            curr_layer.weight.data += alpha * fusion
         # update visited list
         for item in pair_keys:
             visited.append(item)
diff --git a/OWNERS b/OWNERS
index 05a0867100908b9e55041e78e6b97f9cdae78705..9ee948465573ed6f1e31f85e654f30093b17fe98 100644
--- a/OWNERS
+++ b/OWNERS
@@ -19,6 +19,7 @@ approvers:
 - fighting_zhen
 - kezhan1
 - jyoung6652
+- Gongen
 reviewers:
 - ginray0215
 - matrixplayer
@@ -53,4 +54,16 @@ reviewers:
 - han_yifeng
 - jyoung6652
 - maoxx241
-- chenchuw
\ No newline at end of file
+- chenchuw
+- guowenna
+- lanwangli
+- mazhixin00
+- zhou-wenxue
+- huanghao7
+- Gongen
+- kezhan1
+- terrychen1982
+- fan2956
+- Yansifu
+- yliuls
+- shaopeng666
\ No newline at end of file