Update app.py

app.py

@@ -106,6 +106,7 @@ def resize_image(input_path, output_path, target_height):
 
     return output_path
 
+@spaces.GPU
 def infer(use_custom_model, model_name, weight_name, custom_lora_weight, image_in, prompt, negative_prompt, preprocessor, controlnet_conditioning_scale, guidance_scale, inf_steps, seed, progress=gr.Progress(track_tqdm=True)):
 
     pipe = StableDiffusionXLControlNetPipeline.from_pretrained(
@@ -250,7 +251,7 @@ with gr.Blocks(css=css) as demo:
 
         """)
 
-        use_custom_model = gr.Checkbox(label="Use a public custom model ?(optional)", value=False, info="To use a private model, you'll prefer to duplicate the space with your own access token.")
+        use_custom_model = gr.Checkbox(label="Use a custom pre-trained LoRa model ? (optional)", value=False, info="To use a private model, you'll need to duplicate the space with your own access token.")
         
         with gr.Box(visible=False) as custom_model_box:
             with gr.Row():