Instructions to use nguyenkhoa/dinov2_Liveness_detection_v2.2.3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nguyenkhoa/dinov2_Liveness_detection_v2.2.3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="nguyenkhoa/dinov2_Liveness_detection_v2.2.3") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("nguyenkhoa/dinov2_Liveness_detection_v2.2.3") model = AutoModelForImageClassification.from_pretrained("nguyenkhoa/dinov2_Liveness_detection_v2.2.3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 61d4713da294c599713cf0ed896c7300f770027fcded78faa264ec66f4b3a708
- Size of remote file:
- 88.3 MB
- SHA256:
- 804a88acbd0e9dae94ab5c8f4df0fd55f40678f463aeb43400fc8be83a60355b
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