Update app.py

SDXL VAE is redundant on SDXL 0.9 and as far as I can tell, it makes images worse....

app.py

@@ -6,18 +6,16 @@ from PIL import Image
 from diffusers import DiffusionPipeline 
 from huggingface_hub import login
 import os
-from diffusers.models import AutoencoderKL
 
 login(token=os.environ.get('HF_KEY'))
 
 device = "cuda" if torch.cuda.is_available() else "cpu"
 torch.cuda.max_memory_allocated(device='cuda')
-vae = AutoencoderKL.from_pretrained("stabilityai/sdxl-vae", torch_dtype=torch.float16)
 torch.cuda.empty_cache()
 
 def genie (prompt, negative_prompt, height, width, scale, steps, seed, upscaler):
     torch.cuda.max_memory_allocated(device='cuda')
-    pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-0.9", torch_dtype=torch.float16, variant="fp16", use_safetensors=True, vae=vae)
+    pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-0.9", torch_dtype=torch.float16, variant="fp16", use_safetensors=True)
     pipe = pipe.to(device)
     pipe.enable_xformers_memory_efficient_attention()
     torch.cuda.empty_cache()
@@ -26,7 +24,7 @@ def genie (prompt, negative_prompt, height, width, scale, steps, seed, upscaler)
     torch.cuda.empty_cache()
     if upscaler == 'Yes':
         torch.cuda.max_memory_allocated(device='cuda')
-        pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-0.9", torch_dtype=torch.float16, variant="fp16", use_safetensors=True, vae=vae)
+        pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-0.9", torch_dtype=torch.float16, variant="fp16", use_safetensors=True)
         pipe = pipe.to(device)
         pipe.enable_xformers_memory_efficient_attention()
         image = pipe(prompt=prompt, image=int_image).images[0]
@@ -41,7 +39,7 @@ def genie (prompt, negative_prompt, height, width, scale, steps, seed, upscaler)
     else:
         torch.cuda.empty_cache()
         torch.cuda.max_memory_allocated(device=device)
-        pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-0.9", torch_dtype=torch.float16, variant="fp16", use_safetensors=True, vae=vae)
+        pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-0.9", torch_dtype=torch.float16, variant="fp16", use_safetensors=True)
         pipe = pipe.to(device)
         pipe.enable_xformers_memory_efficient_attention()
         image = pipe(prompt=prompt, image=int_image).images[0]