support multi lora

app.py

@@ -85,7 +85,7 @@ def upload_image_to_r2(image, account_id, access_key, secret_key, bucket_name):
     return image_file
 
 
-@spaces.GPU
+
 def generate_image(prompt, steps, seed, cfg_scale, width, height, progress):
     pipe.to("cuda")
     generator = torch.Generator(device="cuda").manual_seed(seed)
@@ -104,7 +104,7 @@ def generate_image(prompt, steps, seed, cfg_scale, width, height, progress):
     progress(99, "Generate success!")
     return generate_image
 
-
+@spaces.GPU
 def run_lora(prompt, cfg_scale, steps, lora_strings, randomize_seed, seed, width, height, lora_scale, upload_to_r2, account_id, access_key, secret_key, bucket, progress=gr.Progress(track_tqdm=True)):
     
 
@@ -167,7 +167,7 @@ with gr.Blocks(css=css) as demo:
                 with gr.Row():
                     seed = gr.Slider(label="Seed", minimum=0, maximum=MAX_SEED, step=1, value=0, randomize=True)
                     randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
-                    lora_scale = gr.Slider(label="LoRA Scale", minimum=0, maximum=3, step=0.01, value=0.95)
+                    lora_scale = gr.Slider(label="LoRA Scale", minimum=0, maximum=1, step=0.01, value=0.5)
 
                 with gr.Row():
                     width = gr.Slider(label="Width", minimum=256, maximum=1536, step=64, value=1024)