Update app.py

app.py

@@ -113,11 +113,12 @@ def load_and_prepare_model(model_id):
     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, torch_dtype=torch.float32),
+     #   vae=AutoencoderKL.from_pretrained("stabilityai/sdxl-vae",repo_type='model',safety_checker=None, torch_dtype=torch.float32),
+        vae=AutoencoderKL.from_pretrained("ford442/sdxl-vae-bf16",repo_type='model',safety_checker=None, torch_dtype=torch.bfloat16),
         #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)