Update README.md

README.md

@@ -28,26 +28,20 @@ You will also need to install [flash-attn](https://github.com/Dao-AILab/flash-at
 Please note that you need at least 80GB VRAM to run this pipeline. CPU offloading is having issues at the moment (PRs welcome!).
 
 ```python
-import torch
 from hyvideo.diffusion.pipelines.pipeline_hunyuan_video import HunyuanVideoPipeline
 from hyvideo.modules.models import HYVideoDiffusionTransformer
 from hyvideo.vae.autoencoder_kl_causal_3d import AutoencoderKLCausal3D
+import diffusers.pipelines
+self.set_nested_attr(diffusers.pipelines, 'hyvideo.HunyuanVideoPipeline', HunyuanVideoPipeline)
+self.set_nested_attr(diffusers.pipelines, 'hyvideo.HYVideoDiffusionTransformer', HYVideoDiffusionTransformer)
+self.set_nested_attr(diffusers.pipelines, 'hyvideo.AutoencoderKLCausal3D', AutoencoderKLCausal3D)
+
+os.environ["HF_HUB_ENABLE_HF_TRANSFER"] = "1"
 
 pipe = HunyuanVideoPipeline.from_pretrained(
-    'magespace/hyvideo-diffusers',
-    transformer=HYVideoDiffusionTransformer.from_pretrained(
-        'magespace/hyvideo-diffusers',
-        torch_dtype=torch.bfloat16,
-        subfolder='transformer'
-    ),
-    vae=AutoencoderKLCausal3D.from_pretrained(
-        'magespace/hyvideo-diffusers',
-        torch_dtype=torch.bfloat16,
-        subfolder='vae'
-    ),
-    torch_dtype=torch.bfloat16,
-)
-pipe = pipe.to('cuda')
+    "magespace/hyvideo-diffusers",
+    torch_dtype=torch.bfloat16
+).to("cuda")
 pipe.vae.enable_tiling()
 ```