Update app.py

app.py

@@ -182,8 +182,8 @@ accelerator = Accelerator(mixed_precision="bf16") # Example
 upscaler = UpscaleWithModel.from_pretrained("Kim2091/ClearRealityV1").to(torch.device("cuda:0"))
 
 def load_and_prepare_model():
-    sched = EulerAncestralDiscreteScheduler.from_pretrained('ford442/RealVisXL_V5.0_BF16', subfolder='scheduler',beta_schedule="scaled_linear", beta_start=0.00085, beta_end=0.012, steps_offset=1 ,use_karras_sigmas=True)
-    vaeXL = AutoencoderKL.from_pretrained("stabilityai/sdxl-vae", safety_checker=None, use_safetensors=False, device_map='cpu') #.to(torch.bfloat16) #.to(device=device, dtype=torch.bfloat16)
+    #sched = EulerAncestralDiscreteScheduler.from_pretrained('ford442/RealVisXL_V5.0_BF16', subfolder='scheduler',beta_schedule="scaled_linear", beta_start=0.00085, beta_end=0.012, steps_offset=1 ,use_karras_sigmas=True)
+    vaeXL = AutoencoderKL.from_pretrained("stabilityai/sdxl-vae", safety_checker=None, use_safetensors=False) #.to(torch.bfloat16) #.to(device=device, dtype=torch.bfloat16)
     #vaeRV = AutoencoderKL.from_pretrained("SG161222/RealVisXL_V5.0", subfolder='vae', safety_checker=None, use_safetensors=False).to(device).to(torch.bfloat16) #.to(device=device, dtype=torch.bfloat16)
     #sched = EulerAncestralDiscreteScheduler.from_pretrained('ford442/RealVisXL_V5.0_BF16', subfolder='scheduler',beta_schedule="scaled_linear")
     #txt_1 = CLIPTextModel.from_pretrained(device_map??)
@@ -195,7 +195,7 @@ def load_and_prepare_model():
         token = HF_TOKEN,
     )
     pipe.vae = vaeXL #.to(torch.bfloat16)
-    pipe.scheduler = sched
+    #pipe.scheduler = sched
     pipe.vae.do_resize = False
     pipe.vae.do_convert_rgb = True
     pipe.vae.set_default_attn_processor()