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
dinov2_Liveness_detection_v2.2.3 / runs /Jan23_07-23-59_e157cb7906f9 /events.out.tfevents.1737617046.e157cb7906f9.18.0
- Xet hash:
- f1b9a3722e2a723d952cc070c9803b317db8e37a4dce5bb548a20a36d7f89b09
- Size of remote file:
- 9.66 kB
- SHA256:
- 1a66ac715a89334cfb7db91ce3c8fbb6a17fe38ef54b8597a32cc30cbd4fffbe
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