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)
-    vae = AutoencoderKL.from_pretrained("stabilityai/sdxl-vae",use_safetensors=True,safety_checker=None)
+    vae = AutoencoderKL.from_pretrained("stabilityai/sdxl-vae",use_safetensors=True)
   #  vae = AutoencoderKL.from_pretrained("BeastHF/MyBack_SDXL_Juggernaut_XL_VAE/MyBack_SDXL_Juggernaut_XL_VAE_V10(version_X).safetensors",safety_checker=None).to(torch.bfloat16)
     #  vae = AutoencoderKL.from_pretrained("ford442/sdxl-vae-bf16", safety_checker=None).to('cuda')
     #sched = EulerAncestralDiscreteScheduler.from_config('ford442/Juggernaut-XI-v11-fp32', subfolder='scheduler',beta_schedule="scaled_linear",use_karras_sigmas=True)
@@ -156,7 +156,7 @@ def load_and_prepare_model(model_id):
     print(f'Pipeline: ')
     print(f'_optional_components: {pipe._optional_components}')
     print(f'watermark: {pipe.watermark}')
-    print(f'safety_checker: {pipe.safety_checker}')
+    print(f'safety_checker: {pipe.vae.safety_checker}')
     print(f'final_image_processor: {pipe.final_image_processor}')
     print(f'feature_extractor: {pipe.feature_extractor}')
     pipe.watermark=None