fix lora scale

app.py

@@ -61,10 +61,10 @@ def load_model(model_id, lora_strength, use_controlnet=False, control_mode="edge
                     controlnet=controlnet,
                     torch_dtype=torch_dtype
                 )
-                pipe.unet = PeftModel.from_pretrained(pipe.unet, model_id, scaling=lora_strength, torch_dtype=torch_dtype)
+                pipe.unet = PeftModel.from_pretrained(pipe.unet, model_id, torch_dtype=torch_dtype)
             else:
                 pipe = StableDiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", torch_dtype=torch_dtype)
-                pipe.unet = PeftModel.from_pretrained(pipe.unet, model_id, scaling=lora_strength)
+                pipe.unet = PeftModel.from_pretrained(pipe.unet, model_id)
 
         elif model_id == "alexanz/SD15_lora_pusheen":
             if use_controlnet:
@@ -74,11 +74,11 @@ def load_model(model_id, lora_strength, use_controlnet=False, control_mode="edge
                     controlnet=controlnet,
                     torch_dtype=torch_dtype
                 )
-                pipe.unet = PeftModel.from_pretrained(pipe.unet, model_id, scaling=lora_strength, torch_dtype=torch_dtype)
+                pipe.unet = PeftModel.from_pretrained(pipe.unet, model_id, torch_dtype=torch_dtype)
             else:
                 if acceleration_mode is None:
                     pipe = StableDiffusionPipeline.from_pretrained("stable-diffusion-v1-5/stable-diffusion-v1-5", torch_dtype=torch_dtype)
-                    pipe.unet = PeftModel.from_pretrained(pipe.unet, model_id, scaling=lora_strength)
+                    pipe.unet = PeftModel.from_pretrained(pipe.unet, model_id)
                 elif acceleration_mode == "distilled":
                     pipe = StableDiffusionPipeline.from_pretrained(
                         "nota-ai/bk-sdm-small", torch_dtype=torch.float16, use_safetensors=True,
@@ -167,7 +167,8 @@ def infer(
         generator=generator,
         image=control_image_cont if use_controlnet else None,
         controlnet_conditioning_scale=control_strength_cont if use_controlnet else None,
-        ip_adapter_image=control_image_ip if use_ip_adapter else None
+        ip_adapter_image=control_image_ip if use_ip_adapter else None,
+        cross_attention_kwargs={"scale": lora_strength}
     ).images[0]
 
     if use_rmbg: