Refactor precision handling and improve user feedback for CUDA availability

app.py

@@ -1,7 +1,6 @@
 import shutil
 import time
 from pathlib import Path
-from xml.parsers.expat import model
 
 import cv2
 import gradio as gr
@@ -17,7 +16,8 @@ from nunchaku.utils import get_gpu_memory, get_precision
 DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
 
 RANK = 128
-TRANSFORMER_ID = f"nunchaku-tech/nunchaku-qwen-image-edit-2509/svdq-{get_precision(device='cpu')}_r{RANK}-qwen-image-edit-2509.safetensors"
+PRECISION = get_precision() if DEVICE == "cuda" else "fp4"
+TRANSFORMER_ID = f"nunchaku-tech/nunchaku-qwen-image-edit-2509/svdq-{PRECISION}_r{RANK}-qwen-image-edit-2509.safetensors"
 PIPELINE_ID = "Qwen/Qwen-Image-Edit-2509"
 
 IMAGE_SIZE = 1024
@@ -167,7 +167,14 @@ class Model:
 
 
 with gr.Blocks() as demo:
-    gr.Markdown("# Nunchaku Qwen-Image-Edit-2509")
+    title = gr.Markdown("# Nunchaku Qwen-Image-Edit-2509")
+
+    gr.Markdown("You can clone this repository or duplicate this space.")
+
+    if DEVICE != "cuda":
+        gr.Markdown(
+            "⚠️ **CUDA not available.** This application requires a CUDA-compatible GPU to function properly."
+        )
 
     with gr.Row():
         with gr.Column():