Update app.py

app.py

@@ -6,7 +6,7 @@ import gradio as gr
 import numpy as np
 import spaces
 import torch
-from diffusers import FluxControlNetModel, FluxPipeline
+from diffusers import FluxControlNetModel, FluxPipeline, AutoencoderTiny
 from diffusers.pipelines import FluxControlNetPipeline
 from diffusers.utils import load_image
 from gradio_imageslider import ImageSlider
@@ -38,13 +38,15 @@ model_path = snapshot_download(
     token=huggingface_token, # type a new token-id.
 )
 
+tokenizer_2 = T5Tokenizer.from_pretrained("LPX55/FLUX.1-merged_uncensored", subfolder="tokenizer_2")
+taef1 = AutoencoderTiny.from_pretrained("madebyollin/taef1", torch_dtype=dtype).to(device)
 
 # Load pipeline
 controlnet = FluxControlNetModel.from_pretrained(
     "jasperai/Flux.1-dev-Controlnet-Upscaler", torch_dtype=torch.bfloat16
 ).to(device)
 pipe = FluxControlNetPipeline.from_pretrained(
-    "LPX55/FLUX.1-merged_uncensored", controlnet=controlnet, torch_dtype=torch.bfloat16, token=huggingface_token,
+    "LPX55/FLUX.1-merged_uncensored", controlnet=controlnet, torch_dtype=torch.bfloat16, vae=taef1, token=huggingface_token,
 )
 # pipe.load_lora_weights(
 #     hf_hub_download("ByteDance/Hyper-SD", "Hyper-FLUX.1-dev-8steps-lora.safetensors"), adapter_name="hyper-sd"