Update app.py

app.py

@@ -107,8 +107,8 @@ def apply_style(style_name: str, positive: str, negative: str = "") -> Tuple[str
 def load_and_prepare_model(model_id):
     model_dtypes = {"ford442/RealVisXL_V5.0_BF16": torch.bfloat16,}
     dtype = model_dtypes.get(model_id, torch.bfloat16)  # Default to float32 if not found
-    #vae = AutoencoderKL.from_pretrained("ford442/sdxl-vae-bf16", safety_checker=None)
-    vaeX = AutoencoderKL.from_pretrained("stabilityai/sdxl-vae")
+    vae = AutoencoderKL.from_pretrained("ford442/sdxl-vae-bf16", safety_checker=None, use_safetensors=False)
+    #vaeX = AutoencoderKL.from_pretrained("stabilityai/sdxl-vae", safety_checker=None)
     #vae = AutoencoderKL.from_pretrained('cross-attention/asymmetric-autoencoder-kl-x-2',use_safetensors=False)
     #vae = AutoencoderKL.from_single_file('https://huggingface.co/ford442/sdxl-vae-bf16/mySLR/myslrVAE_v10.safetensors')
     #vaeX = AutoencoderKL.from_pretrained("stabilityai/sd-vae-ft-mse",use_safetensors=True)
@@ -224,7 +224,7 @@ def uploadNote():
         f.write(f"SPACE SETUP: \n")
         f.write(f"Use Model Dtype: no \n")
         f.write(f"Model Scheduler: Euler_a custom before cuda \n")
-        f.write(f"Model VAE: sdxl-vae to bfloat before cuda then attn_proc vae_scale_factor=4 \n")
+        f.write(f"Model VAE: sdxl-vae-bf16 to bfloat before cuda then attn_proc vae_scale_factor=4 \n")
         f.write(f"Model UNET: default  to bfloat before cuda then attn_proc \n")
         f.write(f"Model HiDiffusion OFF \n")
         f.write(f"Model do_resize OFF \n")