Update app.py

app.py

@@ -106,17 +106,18 @@ def load_and_prepare_model(model_id):
     model_dtypes = {"ford442/RealVisXL_V5.0_BF16": torch.bfloat16,}
     dtype = model_dtypes.get(model_id, torch.bfloat16)  # Default to float32 if not found
     #vae = AutoencoderKL.from_pretrained("ford442/sdxl-vae-bf16", torch_dtype=torch.bfloat16,safety_checker=None).to('cuda')
+    vae = AutoencoderKL.from_pretrained("stabilityai/sdxl-vae", torch_dtype=torch.float32,safety_checker=None).to(torch.bfloat16)
+   # vae = AutoencoderKL.from_pretrained("BeastHF/MyBack_SDXL_Juggernaut_XL_VAE", torch_dtype=torch.float32,safety_checker=None).to(torch.bfloat16)
     #  vae = AutoencoderKL.from_pretrained("ford442/sdxl-vae-bf16", safety_checker=None).to('cuda')
     pipe = StableDiffusionXLPipeline.from_pretrained(
         model_id,
         torch_dtype=torch.bfloat16,
         add_watermarker=False,
         use_safetensors=True,
-    #    vae=vae,
+        vae=vae,
     ).to('cuda')
    # pipe.scheduler=EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
     #pipe.to(device=device, dtype=torch.bfloat16)
-    
     #sched = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config, beta_schedule="scaled_linear", algorithm_type="dpmsolver++")
     sched = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config, beta_schedule="scaled_linear", beta_start =0.00085,beta_end =0.012,steps_offset =1,)
     #sched = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config, beta_schedule="linear", algorithm_type="dpmsolver++")