update

app.py

@@ -17,12 +17,12 @@ ckpt_IPA_dir = '/home/lixiang46/Kolors/weights/Kolors-IP-Adapter-Plus'
 # ckpt_dir = snapshot_download(repo_id="Kwai-Kolors/Kolors")
 # ckpt_IPA_dir = snapshot_download(repo_id="Kwai-Kolors/Kolors-IP-Adapter-Plus")
 
-text_encoder = ChatGLMModel.from_pretrained(f'{ckpt_dir}/text_encoder', torch_dtype=torch.float16).half().to(device)
+text_encoder = ChatGLMModel.from_pretrained(f'{ckpt_dir}/text_encoder', torch_dtype=torch.float16).half()
 tokenizer = ChatGLMTokenizer.from_pretrained(f'{ckpt_dir}/text_encoder')
-vae = AutoencoderKL.from_pretrained(f"{ckpt_dir}/vae", revision=None).half().to(device)
+vae = AutoencoderKL.from_pretrained(f"{ckpt_dir}/vae", revision=None).half()
 scheduler = EulerDiscreteScheduler.from_pretrained(f"{ckpt_dir}/scheduler")
-unet_t2i = UNet2DConditionModel.from_pretrained(f"{ckpt_dir}/unet", revision=None).half().to(device)
-unet_i2i = unet_2d_condition.UNet2DConditionModel.from_pretrained(f"{ckpt_dir}/unet", revision=None).half().to(device)
+unet_t2i = UNet2DConditionModel.from_pretrained(f"{ckpt_dir}/unet", revision=None).half()
+unet_i2i = unet_2d_condition.UNet2DConditionModel.from_pretrained(f"{ckpt_dir}/unet", revision=None).half()
 image_encoder = CLIPVisionModelWithProjection.from_pretrained(f'{ckpt_IPA_dir}/image_encoder',ignore_mismatched_sizes=True).to(dtype=torch.float16, device=device)
 ip_img_size = 336
 clip_image_processor = CLIPImageProcessor(size=ip_img_size, crop_size=ip_img_size)