Fixed for GPU provision

app.py

@@ -1,6 +1,7 @@
 import torch
 import gradio as gr
 from diffusers import FluxPipeline
+import spaces
 
 from nunchaku import NunchakuFluxTransformer2dModel
 from nunchaku.utils import get_precision
@@ -8,14 +9,19 @@ from nunchaku.utils import get_precision
 dtype=torch.bfloat16
 device = "cuda" if torch.cuda.is_available() else "cpu"
 
-precision = get_precision()  # auto-detect your precision is 'int4' or 'fp4' based on your GPU
+@spaces.GPU(duration=10)
+def gpu_precision():
+    precision = get_precision()
+    return precision
+
 transformer = NunchakuFluxTransformer2dModel.from_pretrained(
-    f"nunchaku-tech/nunchaku-flux.1-dev/svdq-{precision}_r32-flux.1-dev.safetensors"
+    f"nunchaku-tech/nunchaku-flux.1-dev/svdq-{gpu_precision()}_r32-flux.1-dev.safetensors"
 )
 pipeline = FluxPipeline.from_pretrained(
     "black-forest-labs/FLUX.1-dev", transformer=transformer, torch_dtype=dtype
 ).to(device)
 
+@spaces.GPU(duration=60)
 def generate_image(prompt: str, steps: int, guidance_scale: float):
     if not prompt.strip():
         raise gr.Error("Prompt cannot be empty.")