Update README.md

README.md

@@ -30,9 +30,9 @@ import tqdm
 seed = 3
 
 # load all models
-unet = UNetUnconditionalModel.from_pretrained("./", subfolder="unet")
-vqvae = VQModel.from_pretrained("./", subfolder="vqvae")
-scheduler = DDIMScheduler.from_config("./", subfolder="scheduler")
+unet = UNetUnconditionalModel.from_pretrained("CompVis/latent-diffusion-celeba-256", subfolder="unet")
+vqvae = VQModel.from_pretrained("CompVis/latent-diffusion-celeba-256", subfolder="vqvae")
+scheduler = DDIMScheduler.from_config("CompVis/latent-diffusion-celeba-256", subfolder="scheduler")
 
 # set to cuda
 torch_device = "cuda" if torch.cuda.is_available() else "cpu"
@@ -87,7 +87,7 @@ import tqdm
 
 seed = 3
 
-pipeline = LatentDiffusionUncondPipeline.from_pretrained("./")
+pipeline = LatentDiffusionUncondPipeline.from_pretrained("CompVis/latent-diffusion-celeba-256")
 
 # generatae image by calling the pipeline
 generator = torch.manual_seed(seed)