Update app.py

app.py

@@ -11,9 +11,7 @@ ckpt = "sdxl_lightning_4step_unet.safetensors"
 # Load model.
 unet = UNet2DConditionModel.from_config(base, subfolder="unet").to("cpu")
 unet.load_state_dict(load_file(hf_hub_download(repo, ckpt), device="cpu"))
-pipe = StableDiffusionXLPipeline.from_pretrained(base, unet=unet, torch_dtype=torch.float32, variant="fp32").to("cpu")
-
-# Ensure sampler uses "trailing" timesteps.
+pipe = StableDiffusionXLPipeline.from_pretrained(base, unet=unet, torch_dtype=torch.float32).to("cpu")
 pipe.scheduler = EulerDiscreteScheduler.from_config(pipe.scheduler.config, timestep_spacing="trailing")
 
 def generate_images(prompt, num_inference_steps, guidance_scale, batch_size):