Update app.py

app.py

@@ -110,7 +110,6 @@ 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(model_id, beta_schedule="scaled_linear",use_karras_sigmas=True, algorithm_type="dpmsolver++"),
 
     #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)
@@ -124,12 +123,13 @@ def load_and_prepare_model(model_id):
        # vae=AutoencoderKL.from_pretrained("ford442/sdxl-vae-bf16",repo_type='model',safety_checker=None),
         vae=vae,
        # unet=pipeX.unet,
-        scheduler =sched,
       #  scheduler = EulerAncestralDiscreteScheduler.from_config(pipeX.scheduler.config, beta_schedule="scaled_linear", beta_start=0.00085, beta_end=0.012, steps_offset=1)
         #scheduler=EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config, beta_schedule="scaled_linear", beta_start=0.00085, beta_end=0.012, steps_offset =1)
     )
+    sched = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config, beta_schedule="scaled_linear",use_karras_sigmas=True, algorithm_type="dpmsolver++"),
     #pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config, beta_schedule="scaled_linear", beta_start=0.00085, beta_end=0.012, steps_offset=1)
     #pipe.to('cuda')
+    pipe.scheduler = sched
     #pipe.vae=vae
     #pipe.vae=pipeX.vae
    # pipe.scheduler=EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)