Update app.py

app.py

@@ -11,9 +11,7 @@ import torch
 from diffusers import DiffusionPipeline
 from typing import Tuple
 
-#Check for the Model Base..//
-
-
+# Check for the Model Base
 
 bad_words = json.loads(os.getenv('BAD_WORDS', "[]"))
 bad_words_negative = json.loads(os.getenv('BAD_WORDS_NEGATIVE', "[]"))
@@ -28,8 +26,6 @@ def check_text(prompt, negative=""):
             return True
     return False
 
-
-
 style_list = [
     {
         "name": "3840 x 2160",
@@ -82,15 +78,10 @@ def apply_style(style_name: str, positive: str, negative: str = "") -> Tuple[str
     return p.replace("{prompt}", positive), n + negative
 
 
-    
 DESCRIPTIONs = """ㅤㅤㅤ """
 
 DESCRIPTION = """ㅤㅤㅤ """
 
-
-
-
-
 if not torch.cuda.is_available():
     DESCRIPTION += "\n<p>⚠️Running on CPU, This may not work on CPU.</p>"
 
@@ -131,6 +122,22 @@ if torch.cuda.is_available():
         pipe.unet = torch.compile(pipe.unet, mode="reduce-overhead", fullgraph=True)
         pipe2.unet = torch.compile(pipe2.unet, mode="reduce-overhead", fullgraph=True)
         print("Model Compiled!")
+else:
+    pipe = DiffusionPipeline.from_pretrained(
+        "SG161222/RealVisXL_V4.0",
+        torch_dtype=torch.float32,
+        use_safetensors=True,
+        add_watermarker=False
+    )
+    pipe2 = DiffusionPipeline.from_pretrained(
+        "SG161222/RealVisXL_V3.0",
+        torch_dtype=torch.float32,
+        use_safetensors=True,
+        add_watermarker=False
+    )
+    pipe.to(device)
+    pipe2.to(device)
+    print("Loaded on Device!")
 
 def save_image(img):
     unique_name = str(uuid.uuid4()) + ".png"
@@ -318,4 +325,4 @@ with gr.Blocks(css=css, theme="xiaobaiyuan/theme_brief") as demo:
     )
     gr.Markdown(DESCRIPTION)
 if __name__ == "__main__":
-    demo.queue(max_size=20).launch()
+    demo.queue(max_size=20).launch()