Update app.py

app.py

@@ -110,20 +110,20 @@ def load_and_prepare_model(model_id):
    #  vae = AutoencoderKL.from_pretrained("stabilityai/sdxl-vae", torch_dtype=torch.float32,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')
-    pipeX = StableDiffusionXLPipeline.from_pretrained("SG161222/RealVisXL_V5.0")
+    pipeX = StableDiffusionXLPipeline.from_pretrained("SG161222/RealVisXL_V5.0", torch_dtype=torch.float32)
     pipe = StableDiffusionXLPipeline.from_pretrained(
         model_id,
-      #  torch_dtype=torch.bfloat16,
+        torch_dtype=torch.bfloat16,
         add_watermarker=False,
         use_safetensors=True,
      #  vae=AutoencoderKL.from_pretrained("BeastHF/MyBack_SDXL_Juggernaut_XL_VAE/MyBack_SDXL_Juggernaut_XL_VAE_V10(version_X).safetensors",repo_type='model',safety_checker=None),
-        vae=AutoencoderKL.from_pretrained("stabilityai/sdxl-vae",repo_type='model',safety_checker=None),
+        vae=AutoencoderKL.from_pretrained("stabilityai/sdxl-vae",repo_type='model',safety_checker=None, torch_dtype=torch.float32),
         #scheduler=EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config, beta_schedule="scaled_linear", beta_start=0.00085, beta_end=0.012, steps_offset =1)
     )
     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=EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
-    pipe.unet = pipeX.unet.to(torch.bfloat16)
+   # pipe.unet = pipeX.unet.to(torch.bfloat16)
     #pipe.to(dtype=torch.bfloat16)
     pipe.to(device)
     pipe.to(torch.bfloat16)