Instructions to use ivanfioravanti/FasterLivePortrait-MLX-weights with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use ivanfioravanti/FasterLivePortrait-MLX-weights with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir FasterLivePortrait-MLX-weights ivanfioravanti/FasterLivePortrait-MLX-weights
- LivePortrait
How to use ivanfioravanti/FasterLivePortrait-MLX-weights with LivePortrait:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
| license: mit | |
| tags: | |
| - mlx | |
| - liveportrait | |
| - image-to-video | |
| - apple-silicon | |
| base_model: | |
| - KlingTeam/LivePortrait | |
| - warmshao/FasterLivePortrait | |
| - jdh-algo/JoyVASA | |
| - TencentGameMate/chinese-hubert-base | |
| # FasterLivePortrait-MLX Weights | |
| Converted MLX `.npz` runtime weights for | |
| [FasterLivePortrait-MLX](https://github.com/ivanfioravanti/fasterliveportrait-mlx). | |
| These files are converted from permissively licensed source checkpoints: | |
| - [KlingTeam/LivePortrait](https://huggingface.co/KlingTeam/LivePortrait), MIT | |
| - [warmshao/FasterLivePortrait](https://huggingface.co/warmshao/FasterLivePortrait), MIT | |
| - [jdh-algo/JoyVASA](https://huggingface.co/jdh-algo/JoyVASA), MIT | |
| - [TencentGameMate/chinese-hubert-base](https://huggingface.co/TencentGameMate/chinese-hubert-base), MIT | |
| ## Included | |
| - Human LivePortrait core MLX weights | |
| - Human landmark MLX weights | |
| - Human stitching / eye / lip retargeting MLX weights | |
| - Animal LivePortrait v1.1 core MLX weights | |
| - JoyVASA MLX audio-to-motion weights for the configured Chinese HuBERT path | |
| - JoyVASA motion template runtime asset | |
| ## Not Included | |
| This repository intentionally does **not** include XPose. XPose is used only for | |
| animal landmark detection in FasterLivePortrait-MLX, and its upstream license is | |
| restricted to non-commercial research use. | |
| This repository also does **not** include the original JoyVASA PyTorch | |
| checkpoint or the original Transformers HuBERT directory. Those are conversion | |
| inputs only. | |
| This repository also does not include the MediaPipe Face Landmarker task model; | |
| download it from Google's MediaPipe model URL as documented in the project | |
| README. | |
| ## Use | |
| ```bash | |
| uv run python scripts/download_mlx_weights.py --repo-id ivanfioravanti/FasterLivePortrait-MLX-weights | |
| ``` | |
| ## Conversion | |
| The weights were produced with: | |
| ```bash | |
| uv run --group convert python scripts/export_mlx_weights.py --include-animal | |
| ``` | |
| JoyVASA weights were produced with: | |
| ```bash | |
| uv run --group convert python scripts/export_mlx_weights.py --include-joyvasa | |
| ``` | |
| Converted tensors are derivative model weights and inherit the obligations of | |
| the original model licenses. | |