Instructions to use chenguolin/sv3d-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use chenguolin/sv3d-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image, export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("chenguolin/sv3d-diffusers", dtype=torch.bfloat16, device_map="cuda") pipe.to("cuda") prompt = "A man with short gray hair plays a red electric guitar." image = load_image( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png" ) output = pipe(image=image, prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
Download vae/diffusion_pytorch_model.safetensors from chenguolin/sv3d-diffusers: direct link, hf CLI and curl.
- Browser
- Download file 335 MB
-
https://huggingface.co/chenguolin/sv3d-diffusers/resolve/main/vae/diffusion_pytorch_model.safetensors
- Command line
-
hf download hf://chenguolin/sv3d-diffusers/vae/diffusion_pytorch_model.safetensors
-
curl -L -o diffusion_pytorch_model.safetensors https://huggingface.co/chenguolin/sv3d-diffusers/resolve/main/vae/diffusion_pytorch_model.safetensors
335 MB
- Xet hash:
- 365729607a65763d8fbe3f9e33a1cb2834b803be5e14ca87cefbccdba3675b9a
- Size of remote file:
- 335 MB
- SHA256:
- b4d2b5932bb4151e54e694fd31ccf51fca908223c9485bd56cd0e1d83ad94c49
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