Image Classification
Transformers
PyTorch
TensorBoard
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use chbh7051/driver-drowsiness-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chbh7051/driver-drowsiness-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="chbh7051/driver-drowsiness-detection") 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("chbh7051/driver-drowsiness-detection") model = AutoModelForImageClassification.from_pretrained("chbh7051/driver-drowsiness-detection") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a6dddd393c5713b8159a925779ae672e908bee6b5766e604add3e1088a0786c4
- Size of remote file:
- 343 MB
- SHA256:
- 5e49275e2b5661042b72a6890d2f3ceb19a7d17e5633b50fd862f064900c3979
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