hw changes

app.py

@@ -1,21 +1,22 @@
+import random
+
 import gradio as gr
 import numpy as np
-import random
+import torch
 
 # import spaces #[uncomment to use ZeroGPU]
 from diffusers import DiffusionPipeline
-import torch
 
 device = "cuda" if torch.cuda.is_available() else "cpu"
-model_repo_id = "stabilityai/sdxl-turbo"  # Replace to the model you would like to use
+# model_repo_id = "stabilityai/sdxl-turbo"  # Replace to the model you would like to use
 
 if torch.cuda.is_available():
     torch_dtype = torch.float16
 else:
     torch_dtype = torch.float32
 
-pipe = DiffusionPipeline.from_pretrained(model_repo_id, torch_dtype=torch_dtype)
-pipe = pipe.to(device)
+# pipe = DiffusionPipeline.from_pretrained(model_repo_id, torch_dtype=torch_dtype)
+# pipe = pipe.to(device)
 
 MAX_SEED = np.iinfo(np.int32).max
 MAX_IMAGE_SIZE = 1024
@@ -23,6 +24,7 @@ MAX_IMAGE_SIZE = 1024
 
 # @spaces.GPU #[uncomment to use ZeroGPU]
 def infer(
+    model_repo_id, 
     prompt,
     negative_prompt,
     seed,
@@ -32,11 +34,14 @@ def infer(
     guidance_scale,
     num_inference_steps,
     progress=gr.Progress(track_tqdm=True),
+
 ):
     if randomize_seed:
         seed = random.randint(0, MAX_SEED)
 
     generator = torch.Generator().manual_seed(seed)
+    pipe = DiffusionPipeline.from_pretrained(model_repo_id, torch_dtype=torch_dtype)
+    pipe = pipe.to(device)
 
     image = pipe(
         prompt=prompt,