Update app.py

app.py

@@ -75,14 +75,15 @@ def upload_to_ftp(filename):
 
 device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
     #vae=AutoencoderKL.from_pretrained("ford442/sdxl-vae-bf16", use_safetensors=True, subfolder='vae',token=True)
-#vaeX=AutoencoderKL.from_pretrained("ford442/stable-diffusion-3.5-large-fp32", safety_checker=None, use_safetensors=True, subfolder='vae', low_cpu_mem_usage=False, torch_dtype=torch.float32, token=True)
+vaeX=AutoencoderKL.from_pretrained("ford442/stable-diffusion-3.5-large-fp32", safety_checker=None, use_safetensors=True, subfolder='vae', low_cpu_mem_usage=False, torch_dtype=torch.float32, token=True)
  
 pipe = StableDiffusion3Pipeline.from_single_file(
     "https://huggingface.co/1inkus/sd35-large-UltraReal-bf16-DDUF/blob/main/sd3-bf16-large.dduf",
     #tokenizer_3=T5TokenizerFast.from_pretrained("ford442/stable-diffusion-3.5-large-bf16", add_prefix_space=False, use_fast=True, subfolder="tokenizer_3"),
     use_safetensors=True,
+    dtype=torch.bfloat16,
     #devive_map='auto',
-).to(device=device, dtype=torch.bfloat16)
+) #.to(device=device)
 
 ###    pipe = StableDiffusion3Pipeline.from_pretrained(
     #"stabilityai  #  stable-diffusion-3.5-large",
@@ -111,8 +112,9 @@ pipe = StableDiffusion3Pipeline.from_single_file(
 #pipe.load_lora_weights("ford442/sdxl-vae-bf16", weight_name="LoRA/UltraReal.safetensors")
 
 #pipe.to(device=device) #, dtype=torch.bfloat16)
-#pipe.to(device)
-#pipe.vae=vaeX.to('cpu')
+pipe.vae=vaeX #.to('cpu')
+
+pipe.to(device)
 upscaler_2 = UpscaleWithModel.from_pretrained("Kim2091/ClearRealityV1").to(torch.device('cuda'))
 
 MAX_SEED = np.iinfo(np.int32).max