Update app.py

app.py

@@ -7,37 +7,32 @@ 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_id_default = "CompVis/stable-diffusion-v1-4"  # 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)
-
-MAX_SEED = np.iinfo(np.int32).max
 MAX_IMAGE_SIZE = 1024
 
 
 # @spaces.GPU #[uncomment to use ZeroGPU]
 def infer(
+    model_id=model_id_default,
     prompt,
     negative_prompt,
-    seed,
-    randomize_seed,
+    seed=42,
     width,
     height,
-    guidance_scale,
-    num_inference_steps,
+    guidance_scale=7.0,
+    num_inference_steps=20,
     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_id, torch_dtype=torch_dtype)
+    pipe = pipe.to(device)
+    
     image = pipe(
         prompt=prompt,
         negative_prompt=negative_prompt,
@@ -47,8 +42,8 @@ def infer(
         height=height,
         generator=generator,
     ).images[0]
-
-    return image, seed
+    
+    return image
 
 
 examples = [