Update app.py

app.py

@@ -5,13 +5,15 @@ from diffusers import StableDiffusionPipeline
 device = "cuda" if torch.cuda.is_available() else "cpu"
 model_id = "nitrosocke/Ghibli-Diffusion"
 
-# Load the model
+# Load the model once and keep it in memory
 pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16 if device == "cuda" else torch.float32)
 pipe.to(device)
+pipe.enable_attention_slicing()  # Optimize memory usage
 
 def generate_ghibli_style(image):
     prompt = "ghibli style portrait"
-    result = pipe(prompt, init_image=image, strength=0.75, guidance_scale=7.0, num_inference_steps=30).images[0]
+    with torch.inference_mode():  # Disables gradient calculations for faster inference
+        result = pipe(prompt, image=image, strength=0.6, guidance_scale=6.5, num_inference_steps=25).images[0]  # Reduced steps & optimized scale
     return result
 
 iface = gr.Interface(