Update app.py

app.py

@@ -8,58 +8,13 @@ from diffusers import StableDiffusion3Pipeline
 import os
 print(os.getenv('HF_TOKEN'))
 
-#Hardware Selection
-device = "cuda" if torch.cuda.is_available() else "cpu"
-
-# GPU support
-if torch.cuda.is_available():
-    torch.cuda.max_memory_allocated(device=device)
-    pipe = StableDiffusion3Pipeline.from_pretrained("stabilityai/stable-diffusion-3-medium-diffusers", token=HF_TOKEN, torch_dtype=torch.float16)
-    pipe.enable_xformers_memory_efficient_attention()
-    pipe = pipe.to(device)
-
-# CPU Support
-else: 
-    pipe = StableDiffusion3Pipeline.from_pretrained("stabilityai/stable-diffusion-3-medium-diffusers", torch_dtype=torch.float16)
-    pipe = pipe.to(device)
-
-MAX_SEED = np.iinfo(np.int32).max
-MAX_IMAGE_SIZE = 2048
-
-def infer(prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps):
-
-    if randomize_seed:
-        seed = random.randint(0, MAX_SEED)
-        
-    generator = torch.Generator().manual_seed(seed)
-    
-    image = pipe(
-        prompt = prompt, 
-        negative_prompt = negative_prompt,
-        guidance_scale = guidance_scale, 
-        num_inference_steps = num_inference_steps, 
-        width = width, 
-        height = height,
-        generator = generator
-    ).images[0] 
-    
-    return image
-
-css="""
-#col-container {
-    margin: 0 auto;
-    max-width: 520px;
-}
-"""
+gr.load("models/stabilityai/stable-diffusion-3-diffusers")
 
 
 with gr.Blocks(css=css) as demo:
     
     with gr.Column(elem_id="col-container"):
-        gr.Markdown(f"""
-        # FallnAI Text2Image
-        """)
-        
+
         with gr.Row():
             
             prompt = gr.Text(