float type mismatch

app.py

@@ -42,11 +42,16 @@ base = "stabilityai/stable-diffusion-xl-base-1.0"
 repo = "ByteDance/SDXL-Lightning"
 ckpt = "sdxl_lightning_4step_unet.safetensors"  # Use the correct ckpt for your step setting!
 
-unet = UNet2DConditionModel.from_config(base, subfolder="unet").to("cuda", torch.float16)
+# unet = UNet2DConditionModel.from_config(base, subfolder="unet").to("cuda", torch.float16)
+# unet.load_state_dict(load_file(hf_hub_download(repo, ckpt), device="cuda"))
+# pipe = StableDiffusionXLPipeline.from_pretrained(base, unet=unet, torch_dtype=torch.float16, variant="fp16")
+# pipe.scheduler = EulerDiscreteScheduler.from_config(pipe.scheduler.config, timestep_spacing="trailing")
+# pipe = pipe.to(device)
+
+unet = UNet2DConditionModel.from_config(base, subfolder="unet").to("cuda")
 unet.load_state_dict(load_file(hf_hub_download(repo, ckpt), device="cuda"))
-pipe = StableDiffusionXLPipeline.from_pretrained(base, unet=unet, torch_dtype=torch.float16, variant="fp16")
+pipe = StableDiffusionXLPipeline.from_pretrained(base, unet=unet).to("cuda")
 pipe.scheduler = EulerDiscreteScheduler.from_config(pipe.scheduler.config, timestep_spacing="trailing")
-pipe = pipe.to(device)
 
 # Load resadapter
 pipe.load_lora_weights(