Update app.py

app.py

@@ -65,13 +65,13 @@ checkpoint = "microsoft/Phi-3.5-mini-instruct"
 pipe = StableDiffusion3Pipeline.from_pretrained(
     "stabilityai/stable-diffusion-3.5-large",
     #"ford442/stable-diffusion-3.5-large-bf16",
-    vae=AutoencoderKL.from_pretrained("ford442/stable-diffusion-3.5-large-bf16", subfolder='vae',token=True)
-    transformer=SD3Transformer2DModel.from_pretrained("ford442/stable-diffusion-3.5-large-bf16", subfolder='transformer',token=True)
+    vae=AutoencoderKL.from_pretrained("ford442/stable-diffusion-3.5-large-bf16", subfolder='vae',token=True),
+    transformer=SD3Transformer2DModel.from_pretrained("ford442/stable-diffusion-3.5-large-bf16", subfolder='transformer',token=True),
     text_encoder=CLIPTextModelWithProjection.from_pretrained("ford442/stable-diffusion-3.5-large-bf16", subfolder='text_encoder',token=True),
     text_encoder_2=CLIPTextModelWithProjection.from_pretrained("ford442/stable-diffusion-3.5-large-bf16", subfolder='text_encoder_2',token=True),
     text_encoder_3=T5EncoderModel.from_pretrained("ford442/stable-diffusion-3.5-large-bf16", subfolder='text_encoder_3',token=True),
     token=True,
-    use_safetensors=False,
+    #use_safetensors=False,
 )
 
 pipe.to(device=device, dtype=torch.bfloat16)