Instructions to use vanzl/DiffusionART-HunyuanVideo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use vanzl/DiffusionART-HunyuanVideo with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("vanzl/DiffusionART-HunyuanVideo", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Download examples/00113-pretrained.mp4 from vanzl/DiffusionART-HunyuanVideo: direct link, hf CLI and curl.
- Browser
- Download file 722 kB
-
https://huggingface.co/vanzl/DiffusionART-HunyuanVideo/resolve/main/examples/00113-pretrained.mp4
- Command line
-
hf download hf://vanzl/DiffusionART-HunyuanVideo/examples/00113-pretrained.mp4
-
curl -L -o 00113-pretrained.mp4 https://huggingface.co/vanzl/DiffusionART-HunyuanVideo/resolve/main/examples/00113-pretrained.mp4
722 kB
- Xet hash:
- 1ce250e00f8dbb33827c284406cb5c81b28c1f20fe05d7d7297f056822de975a
- Size of remote file:
- 722 kB
- SHA256:
- 4c484efff6af258fd58f2b921ab2c28b97ee3dae434f66d304f2a728ea5baf46
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.