Instructions to use minchul/cvlface_adaface_vit_base_webface4m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use minchul/cvlface_adaface_vit_base_webface4m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="minchul/cvlface_adaface_vit_base_webface4m", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("minchul/cvlface_adaface_vit_base_webface4m", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| README.md | |
| pretrained_model/model.pt | |
| pretrained_model/model.yaml | |
| pretrained_model/config.yaml | |
| models/__init__.py | |
| models/vit/vit.py | |
| models/vit/__init__.py | |
| models/vit/configs/v1_small.yaml | |
| models/vit/configs/v1_base.yaml | |
| models/base/utils.py | |
| models/base/__init__.py | |
| models/base/configs/example.yaml | |