Fix description

app.py

@@ -27,9 +27,6 @@ from diffusers.pipelines.stable_diffusion.safety_checker import StableDiffusionS
 
 BASE_MODEL = "SG161222/Realistic_Vision_V5.1_noVAE"
 
-# Initialize both pipelines
-vae = AutoencoderKL.from_pretrained("stabilityai/sd-vae-ft-mse", torch_dtype=torch.float16)
-controlnet = ControlNetModel.from_pretrained("monster-labs/control_v1p_sd15_qrcode_monster", torch_dtype=torch.float16)
 
 # Initialize the safety checker conditionally
 SAFETY_CHECKER_ENABLED = os.environ.get("SAFETY_CHECKER", "0") == "1"
@@ -39,20 +36,36 @@ device='cuda'
 device='cpu'
 
 
+# Initialize both pipelines
+if device=='cuda':
+    vae = AutoencoderKL.from_pretrained("stabilityai/sd-vae-ft-mse", torch_dtype=torch.float16)
+    controlnet = ControlNetModel.from_pretrained("monster-labs/control_v1p_sd15_qrcode_monster", torch_dtype=torch.float16)
+else:
+    vae = AutoencoderKL.from_pretrained("stabilityai/sd-vae-ft-mse")
+    controlnet = ControlNetModel.from_pretrained("monster-labs/control_v1p_sd15_qrcode_monster")
+
+
 if SAFETY_CHECKER_ENABLED:
     safety_checker = StableDiffusionSafetyChecker.from_pretrained("CompVis/stable-diffusion-safety-checker").to(device)
     feature_extractor = CLIPImageProcessor.from_pretrained("openai/clip-vit-base-patch32")
 
-
-main_pipe = StableDiffusionControlNetPipeline.from_pretrained(
-    BASE_MODEL,
-    controlnet=controlnet,
-    vae=vae,
-    safety_checker=safety_checker,
-    feature_extractor=feature_extractor,
-    torch_dtype=torch.float16,
-).to(device)
-
+if device=='cuda':
+    main_pipe = StableDiffusionControlNetPipeline.from_pretrained(
+        BASE_MODEL,
+        controlnet=controlnet,
+        vae=vae,
+        safety_checker=safety_checker,
+        feature_extractor=feature_extractor,
+        torch_dtype=torch.float16,
+    ).to(device)
+else:
+    main_pipe = StableDiffusionControlNetPipeline.from_pretrained(
+        BASE_MODEL,
+        controlnet=controlnet,
+        vae=vae,
+        safety_checker=safety_checker,
+        feature_extractor=feature_extractor
+    ).to(device)    
 # Function to check NSFW images
 #def check_nsfw_images(images: list[Image.Image]) -> tuple[list[Image.Image], list[bool]]:
 #    if SAFETY_CHECKER_ENABLED:
@@ -225,15 +238,14 @@ def inference(
 with gr.Blocks() as app:
     gr.Markdown(
         '''
-        <div style="text-align: center;">
+        <div>
             <h1>pattern + prompt = image</h1>
-            <p style="font-size:16px;">Generate stunning high quality illusion artwork with Stable Diffusion</p>
-            <p>Illusion Diffusion is back up with a safety checker! Because I have been asked, if you would like to support me, consider using <a href="https://deforum.studio">deforum.studio</a></p>
-            <p>With big contributions from 
+            <p>With big contributions from:</p>
             <ul>
             <li><a href="https://twitter.com/multimodalart">multimodalart</a></li>
             <li><a href="https://huggingface.co/monster-labs/control_v1p_sd15_qrcode_monster">Monster Labs QR Control Net</a></li>
-            <li><a href="https://twitter.com/MrUgleh">MrUgleh</a>/li>
+            <li><a href="https://twitter.com/MrUgleh">MrUgleh</a></li>
+            <li><a href="https://huggingface.co/spaces/AP123/IllusionDiffusion">https://huggingface.co/spaces/AP123/IllusionDiffusion</a> - use it for GPU speed!</li>
             </ul>
         </div>
         '''