Update app.py

app.py

@@ -39,6 +39,7 @@ def get_lora_sd_pipeline(
     pipe = StableDiffusionPipeline.from_pretrained(base_model_name_or_path, torch_dtype=dtype).to(device)
     pipe.unet = PeftModel.from_pretrained(pipe.unet, unet_sub_dir, adapter_name=adapter_name)
     pipe.unet.set_adapter(adapter_name)
+    pipe.fuse_lora(lora_scale=lora_scale)
 
     if os.path.exists(text_encoder_sub_dir):
         pipe.text_encoder = PeftModel.from_pretrained(
@@ -99,7 +100,6 @@ def infer(
     pipe = pipe.to(device)
     prompt_embeds = encode_prompt(prompt, pipe.tokenizer, pipe.text_encoder)
     negative_prompt_embeds = encode_prompt(negative_prompt, pipe.tokenizer, pipe.text_encoder)
-    pipe.fuse_lora(lora_scale=lora_scale)
     
     image = pipe(
         prompt_embeds=prompt_embeds,
@@ -210,7 +210,9 @@ with gr.Blocks(css=css, fill_height=True) as demo:
             model_id,
             seed,
             guidance_scale,
-            num_inference_steps,       
+            num_inference_steps,      
+            lora_scale
+            
         ],
         outputs=[result],
     )