Update app.py

app.py

@@ -108,7 +108,7 @@ 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")
+    #vaeX = AutoencoderKL.from_pretrained("stabilityai/sdxl-vae")
     #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)
@@ -153,9 +153,9 @@ def load_and_prepare_model(model_id):
     #pipe.unet = unetX
     pipe.scheduler = sched
     pipe.vae.do_resize=False
-    #pipe.vae.do_rescale=False
-    #pipe.vae.do_convert_rgb=True
-    pipe.vae.vae_scale_factor=2
+    pipe.vae.do_rescale=False
+    pipe.vae.do_convert_rgb=True
+    pipe.vae.vae_scale_factor=1
     #pipe.scheduler = sched
     #pipe.vae=vae.to(torch.bfloat16)
     #pipe.unet=pipeX.unet
@@ -228,7 +228,7 @@ def uploadNote():
         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")
-        f.write(f"Model vae_scale_factor 2 \n")
+        f.write(f"Model vae_scale_factor 1 / do-rescale=False \n")
     upload_to_ftp(filename) 
     
 @spaces.GPU(duration=30)