Update app.py

app.py

@@ -77,13 +77,13 @@ 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)
  
-###pipe = StableDiffusion3Pipeline.from_single_file(
-    ###"1inkus/sd35-large-UltraReal-bf16-DDUF",
-    ###tokenizer_3=T5TokenizerFast.from_pretrained("ford442/stable-diffusion-3.5-large-bf16", add_prefix_space=False, use_fast=True, subfolder="tokenizer_3", token=True),
-    ###use_safetensors=True,
-###)
+pipe = StableDiffusion3Pipeline.from_single_file(
+    "https://huggingface.co/1inkus/sd35-large-UltraReal-bf16-DDUF/resolve/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,
+)
 
-    pipe = StableDiffusion3Pipeline.from_pretrained(
+###    pipe = StableDiffusion3Pipeline.from_pretrained(
     #"stabilityai  #  stable-diffusion-3.5-large",
     #"ford442/stable-diffusion-3.5-large-bf16",
     "ford442/stable-diffusion-3.5-large-fp32",
@@ -99,10 +99,10 @@ device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
     #tokenizer=CLIPTokenizer.from_pretrained("ford442/stable-diffusion-3.5-large-bf16", add_prefix_space=True, subfolder="tokenizer", token=True),
     #tokenizer_2=CLIPTokenizer.from_pretrained("ford442/stable-diffusion-3.5-large-bf16", add_prefix_space=True, subfolder="tokenizer_2", token=True),
     #tokenizer_3=T5TokenizerFast.from_pretrained("ford442/stable-diffusion-3.5-large-bf16", add_prefix_space=False, use_fast=True, subfolder="tokenizer_3", token=True),
-    tokenizer_3=T5TokenizerFast.from_pretrained("ford442/stable-diffusion-3.5-large-bf16", add_prefix_space=False, use_fast=True, subfolder="tokenizer_3", token=True),
+###    tokenizer_3=T5TokenizerFast.from_pretrained("ford442/stable-diffusion-3.5-large-bf16", add_prefix_space=False, use_fast=True, subfolder="tokenizer_3", token=True),
     #torch_dtype=torch.bfloat16,
     #use_safetensors=False,
-)
+###)
 #text_encoder=CLIPTextModelWithProjection.from_pretrained("ford442/stable-diffusion-3.5-large-bf16", subfolder='text_encoder', token=True).to(torch.device("cuda:0")) #, dtype=torch.bfloat16)
 #text_encoder_2=CLIPTextModelWithProjection.from_pretrained("ford442/stable-diffusion-3.5-large-bf16", subfolder='text_encoder_2',token=True).to(torch.device("cuda:0")) #, dtype=torch.bfloat16)
 #text_encoder_3=T5EncoderModel.from_pretrained("ford442/stable-diffusion-3.5-large-fp32", subfolder='text_encoder_3',token=True).to(torch.device("cuda:0")) #, dtype=torch.bfloat16)