Update app.py

app.py

@@ -50,18 +50,12 @@ with open('loras.json', 'r') as f:
 pipe = diffusers.ZImagePipeline.from_pretrained("dimitribarbot/Z-Image-Turbo-BF16", torch_dtype=torch.bfloat16)
 
 #pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taef1", torch_dtype=torch.float16).to("cuda")
-#pipe.vae = AutoencoderKL.from_pretrained("AlekseyCalvin/AnimeVAE_by_Anzhc_for_Flux_ZiT", torch_dtype=torch.bfloat16, device_map="cuda")
+pipe.vae = AutoencoderKL.from_pretrained("AlekseyCalvin/Custom_VAE-Z-image-FLUX.1-by-G-REPA", torch_dtype=torch.bfloat16, device_map="cuda")
 
-custom_vae = AutoencoderKL.from_pretrained(
-    "AlekseyCalvin/AnimeVAE_by_Anzhc_for_Flux_ZiT",
-    torch_dtype=torch.float32,
-    ignore_mismatched_sizes=True,
-    low_cpu_mem_usage=False,
-    device_map=None # Do not use device_map here
-)
+#custom_vae = AutoencoderKL.from_pretrained("AlekseyCalvin/AnimeVAE_by_Anzhc_for_Flux_ZiT", torch_dtype=torch.float32, ignore_mismatched_sizes=True, low_cpu_mem_usage=False, device_map=None)
 
 # Manually move the VAE to the correct device (e.g., "cuda")
-pipe.vae = custom_vae.to("cuda")
+#pipe.vae = custom_vae.to("cuda")
 device = "cuda" if torch.cuda.is_available() else "cpu"