diff --git a/networks/resize_lora.py b/networks/resize_lora.py
index 39d4c9072..03fc545e7 100644
--- a/networks/resize_lora.py
+++ b/networks/resize_lora.py
@@ -219,7 +219,7 @@ def resize_lora_model(lora_sd, new_rank, save_dtype, device, dynamic_method, dyn
     for key, value in tqdm(lora_sd.items()):
       weight_name = None
       if 'lora_down' in key:
-        block_down_name = key.rsplit('lora_down', 1)[0]
+        block_down_name = key.rsplit('.lora_down', 1)[0]
         weight_name = key.rsplit(".", 1)[-1]
         lora_down_weight = value
       else:
@@ -227,8 +227,8 @@ def resize_lora_model(lora_sd, new_rank, save_dtype, device, dynamic_method, dyn
 
       # find corresponding lora_up and alpha
       block_up_name = block_down_name
-      lora_up_weight = lora_sd.get(block_up_name + 'lora_up.' + weight_name, None)
-      lora_alpha = lora_sd.get(block_down_name + 'alpha', None)
+      lora_up_weight = lora_sd.get(block_up_name + '.lora_up.' + weight_name, None)
+      lora_alpha = lora_sd.get(block_down_name + '.alpha', None)
 
       weights_loaded = (lora_down_weight is not None and lora_up_weight is not None)
 
@@ -263,9 +263,9 @@ def resize_lora_model(lora_sd, new_rank, save_dtype, device, dynamic_method, dyn
           verbose_str+=f"\n"
 
         new_alpha = param_dict['new_alpha']
-        o_lora_sd[block_down_name + "lora_down.weight"] = param_dict["lora_down"].to(save_dtype).contiguous()
-        o_lora_sd[block_up_name + "lora_up.weight"] = param_dict["lora_up"].to(save_dtype).contiguous()
-        o_lora_sd[block_up_name + "alpha"] = torch.tensor(param_dict['new_alpha']).to(save_dtype)
+        o_lora_sd[block_down_name + "." + "lora_down.weight"] = param_dict["lora_down"].to(save_dtype).contiguous()
+        o_lora_sd[block_up_name + "." + "lora_up.weight"] = param_dict["lora_up"].to(save_dtype).contiguous()
+        o_lora_sd[block_up_name + "." "alpha"] = torch.tensor(param_dict['new_alpha']).to(save_dtype)
 
         block_down_name = None
         block_up_name = None