Instructions to use FrancisRing/StableAnimator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use FrancisRing/StableAnimator 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("FrancisRing/StableAnimator", 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 Animation/unet.pth from FrancisRing/StableAnimator: direct link, hf CLI and curl.
- Browser
- Download file 6.2 GB
-
https://huggingface.co/FrancisRing/StableAnimator/resolve/main/Animation/unet.pth
- Command line
-
hf download hf://FrancisRing/StableAnimator/Animation/unet.pth
-
curl -L -o unet.pth https://huggingface.co/FrancisRing/StableAnimator/resolve/main/Animation/unet.pth
6.2 GB
- Xet hash:
- 86cbe295da20793e09fd82b98adf09405cdac8cd850530e9e63bc835f82d7147
- Size of remote file:
- 6.2 GB
- SHA256:
- 6c46bde145df2f9c52bd123aaf0e6f23ea88a786af4d37bdceac294bab5947fa
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