Update app.py

app.py

@@ -58,8 +58,9 @@ torch_dtype = torch.bfloat16
 
 checkpoint = "microsoft/Phi-3.5-mini-instruct"
 #vae = AutoencoderKL.from_pretrained("madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16)
-vae = AutoencoderKL.from_pretrained("ford442/sdxl-vae-bf16")
 #vae = AutoencoderKL.from_pretrained("ford442/sdxl-vae-bf16")
+#vae = AutoencoderKL.from_pretrained("ford442/sdxl-vae-bf16")
+vae = AutoencoderKL.from_pretrained("stabilityai/sdxl-vae",use_safetensors=True,safety_checker=None)
 
 pipe = StableDiffusion3Pipeline.from_pretrained("ford442/stable-diffusion-3.5-medium-bf16").to(device=torch.device("cuda:0")).to(torch.bfloat16)
 #pipe = StableDiffusion3Pipeline.from_pretrained("ford442/stable-diffusion-3.5-medium-bf16").to(torch.device("cuda:0"))
@@ -75,9 +76,12 @@ pipe = StableDiffusion3Pipeline.from_pretrained("ford442/stable-diffusion-3.5-me
 #pipe = torch.compile(pipe)
 # pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config, beta_schedule="scaled_linear")
 
-refiner = StableDiffusionXLImg2ImgPipeline.from_pretrained("ford442/stable-diffusion-xl-refiner-1.0-bf16", vae=AutoencoderKL.from_pretrained("ford442/sdxl-vae-bf16"), use_safetensors=True, requires_aesthetics_score=True).to(device=torch.device("cuda:0")).to(torch.bfloat16)
+refiner = StableDiffusionXLImg2ImgPipeline.from_pretrained("ford442/stable-diffusion-xl-refiner-1.0-bf16", use_safetensors=True, requires_aesthetics_score=True)
+refiner.vae=vae
+refiner.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config, beta_schedule="scaled_linear", algorithm_type="sde-dpmsolver++")
+refiner.to(device=torch.device("cuda:0"))
+refiner.to(torch.bfloat16)
 #refiner = StableDiffusionXLImg2ImgPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-1.0", vae=vae, torch_dtype=torch.float32, requires_aesthetics_score=True, device_map='balanced')
-refiner.scheduler=EulerAncestralDiscreteScheduler.from_config(refiner.scheduler.config, beta_schedule="scaled_linear")
 #refiner.enable_model_cpu_offload()
 
 #refiner.scheduler.config.requires_aesthetics_score=False