Instructions to use silk-road/simple-face-recognition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use silk-road/simple-face-recognition with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("silk-road/simple-face-recognition", "lda_openai_clip_model.pkl") ) # only load pickle files from sources you trust # read more about it here https://skops.readthedocs.io/en/stable/persistence.html - Notebooks
- Google Colab
- Kaggle
Model description
ไธไธช็ฎๆ่ฏด็ไบบ่ธ่ฏๅซbaseline๏ผไฝฟ็จopenai/clip-vit-base-patch16 + LDA็็ญ็ฅ
Intended uses & limitations
ๆดไฝ้่ฆ้ ๅgithubๅฏนๅบ็ไปฃ็ ไฝฟ็จ
Training Procedure
[More Information Needed]
Hyperparameters
Click to expand
| Hyperparameter | Value |
|---|---|
| covariance_estimator | |
| n_components | 512 |
| priors | |
| shrinkage | |
| solver | svd |
| store_covariance | False |
| tol | 0.0001 |
Model Plot
LinearDiscriminantAnalysis(n_components=512)In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
LinearDiscriminantAnalysis(n_components=512)
Evaluation Results
[More Information Needed]
How to Get Started with the Model
[More Information Needed]
Model Card Authors
Cheng Li(https://github.com/LC1332)
Model Card Contact
You can contact the model card authors through following channels: [More Information Needed]
Citation
@inproceedings{wang2018devil, title={The devil of face recognition is in the noise}, author={Wang, Fei and Chen, Liren and Li, Cheng and Huang, Shiyao and Chen, Yanjie and Qian, Chen and Loy, Chen Change}, booktitle={Proceedings of the European Conference on Computer Vision (ECCV)}, pages={765--780}, year={2018} }
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