Update app.py

app.py

@@ -31,7 +31,7 @@ torch.backends.cudnn.deterministic = False
 torch.backends.cudnn.benchmark = False
 torch.set_float32_matmul_precision("highest")
 
-from diffusers import StableDiffusion3Pipeline, SD3Transformer2DModel, AutoencoderKL, FlowMatchEulerDiscreteScheduler
+from diffusers import StableDiffusion3Pipeline, SD3Transformer2DModel, AutoencoderKL
 from PIL import Image
 from image_gen_aux import UpscaleWithModel
 
@@ -73,16 +73,12 @@ pipe = StableDiffusion3Pipeline.from_pretrained(
     "ford442/stable-diffusion-3.5-large-bf16",
     trust_remote_code=True,
     transformer=None, # Load transformer separately
-    #scheduler=None,
     use_safetensors=True
 )
 
-#scheduler2=FlowMatchEulerDiscreteScheduler.from_pretrained("ford442/stable-diffusion-3.5-large-bf16", subfolder='scheduler')
-#pipe.scheduler=scheduler2
 ll_transformer=SD3Transformer2DModel.from_pretrained("ford442/stable-diffusion-3.5-large-bf16", subfolder='transformer').to(device, dtype=torch.bfloat16)
 pipe.transformer=ll_transformer
 pipe.load_lora_weights("ford442/sdxl-vae-bf16", weight_name="LoRA/UltraReal.safetensors")
-
 pipe.to(device=device, dtype=torch.bfloat16)
 
 upscaler_2 = UpscaleWithModel.from_pretrained("Kim2091/ClearRealityV1").to(device)