back to "GuangyuanSD/Z-Image-Re-Turbo-LoRA" model

app.py

@@ -2,11 +2,11 @@ import gradio as gr
 import numpy as np
 import random
 
-# import spaces #[uncomment to use ZeroGPU]
+import spaces #[uncomment to use ZeroGPU]
 from diffusers import DiffusionPipeline
 import torch
 
-pipe = DiffusionPipeline.from_pretrained("ostris/Z-Image-De-Turbo", dtype=torch.bfloat16, device_map="cuda")
+pipe = DiffusionPipeline.from_pretrained("GuangyuanSD/Z-Image-Re-Turbo-LoRA", dtype=torch.bfloat16, device_map="cuda")
 
 MAX_SEED = np.iinfo(np.int32).max
 MAX_IMAGE_SIZE = 1024