Update app.py

app.py

@@ -111,13 +111,14 @@ def load_and_prepare_model(model_id):
     #vae = AutoencoderKL.from_pretrained("stabilityai/sdxl-vae",safety_checker=None)
   #  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)
+    #sched = EulerAncestralDiscreteScheduler.from_config('ford442/Juggernaut-XI-v11-fp32', subfolder='scheduler',beta_schedule="scaled_linear",use_karras_sigmas=True)
+    sched = EulerAncestralDiscreteScheduler.from_config('ford442/RealVisXL_V5.0_BF16', subfolder='scheduler',beta_schedule="scaled_linear",use_karras_sigmas=True)
 
     #pipeX = StableDiffusionXLPipeline.from_pretrained("SG161222/RealVisXL_V5.0",torch_dtype=torch.float32)
     #pipeX = StableDiffusionXLPipeline.from_pretrained("ford442/Juggernaut-XI-v11-fp32",torch_dtype=torch.float32)
     pipe = StableDiffusionXLPipeline.from_pretrained(
-    #    'ford442/RealVisXL_V5.0_BF16',
-        'ford442/Juggernaut-XI-v11-fp32',
+        'ford442/RealVisXL_V5.0_BF16',
+    #    'ford442/Juggernaut-XI-v11-fp32',
         #torch_dtype=torch.bfloat16,
         add_watermarker=False,
        # custom_pipeline="lpw_stable_diffusion_xl",