Update app.py

app.py

@@ -4,7 +4,7 @@ import numpy as np
 import random
 
 import torch
-from diffusers import StableDiffusion3Pipeline
+from diffusers import StableDiffusion3Pipeline, AutoencoderKL
 #from transformers import CLIPTextModelWithProjection, T5EncoderModel
 from transformers import CLIPTokenizer, T5TokenizerFast
 
@@ -61,6 +61,7 @@ def upload_to_ftp(filename):
 pyx = cyper.inline(code, fast_indexing=True, directives=dict(boundscheck=False, wraparound=False, language_level=3))
 
 device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
+vaeX=AutoencoderKL.from_pretrained("ford442/sdxl-vae-bf16", use_safetensors=True, subfolder='sd3-vae',token=True)
 
 pipe = StableDiffusion3Pipeline.from_pretrained(
     #"stabilityai  #  stable-diffusion-3.5-large",
@@ -73,6 +74,7 @@ pipe = StableDiffusion3Pipeline.from_pretrained(
     #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),
+    vae=vaeX,
     #torch_dtype=torch.bfloat16,
     #use_safetensors=False,
 )