Update app.py

app.py

@@ -37,6 +37,7 @@ 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)
 
     if os.path.exists(text_encoder_sub_dir):
         pipe.text_encoder = PeftModel.from_pretrained(
@@ -50,7 +51,7 @@ def get_lora_sd_pipeline(
     pipe.to(device)
     return pipe
 
-
+    
 def encode_prompt(prompt, tokenizer, text_encoder):
     text_inputs = tokenizer(
         prompt,
@@ -158,7 +159,7 @@ with gr.Blocks(css=css, fill_height=True) as demo:
                 step=0.1,
                 value=7.0,  # Replace with defaults that work for your model
             )
-
+        with gr.Row():
             lora_scale = gr.Slider(
                 label="LoRA scale",
                 minimum=0.0,