Update app.py

app.py

@@ -7,7 +7,6 @@ import torch
 from diffusers import DiffusionPipeline
 from transformers import CLIPTextModel, CLIPTokenizer, T5EncoderModel, T5TokenizerFast
 
-
 # Define the device
 device = "cuda" if torch.cuda.is_available() else "cpu"
 
@@ -29,9 +28,10 @@ pipe = DiffusionPipeline.from_pretrained(
     token=hf_token
 ).to(device)
 
-@spaces.GPU(duration=190)
-MAX_SEED = 2**32-1
+# Define MAX_SEED
+MAX_SEED = 2**32 - 1
 
+@spaces.GPU(duration=190)
 def run_lora(prompt, cfg_scale, steps, selected_repo, randomize_seed, seed, width, height, lora_scale):
     if not selected_repo:
         raise gr.Error("You must select a LoRA before proceeding.")