Instructions to use py-feat/mobilefacenet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Py-Feat
How to use py-feat/mobilefacenet with Py-Feat:
# 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
mobilefacenet
Licensing scope: See the license and provenance notice before relying on this card's license metadata for pretrained-weight redistribution or commercial use. Existing valid grants are preserved.
This model has been pushed to the Hub using the PytorchModelHubMixin integration:
- Library: [More Information Needed]
- Docs: [More Information Needed]
License and provenance
The mobilefacenet_model_best.pth.tar checkpoint comes from cunjian/pytorch_face_landmark. A sufficiently explicit upstream redistribution license for this landmark checkpoint has not been established in the reviewed public material. Licenses for separate utilities or the upstream repository's RetinaFace subdirectory do not establish a grant for this checkpoint. See the upstream license question.
Py-Feat's MIT license covers its own contributions; it does not relicense third-party checkpoint weights. Upstream clarification and the exact checkpoint's training-data provenance are needed. No new weight license is assigned by this notice.
This notice clarifies scope; it does not revoke existing valid grants or create a new license for third-party material. Dataset and teacher terms do not automatically relicense every trained artifact or inference output. A software license or model-card badge alone does not establish all checkpoint redistribution or commercial-use permissions.
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