Instructions to use Ganaa614/vit-tiny-patch16-224cabin_activity_recognition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ganaa614/vit-tiny-patch16-224cabin_activity_recognition with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Ganaa614/vit-tiny-patch16-224cabin_activity_recognition") 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("Ganaa614/vit-tiny-patch16-224cabin_activity_recognition") model = AutoModelForImageClassification.from_pretrained("Ganaa614/vit-tiny-patch16-224cabin_activity_recognition", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 525e182427d45f0ce42ca2d518d4623be245f9593b24bf669d09eabfde30be8c
- Size of remote file:
- 5.84 kB
- SHA256:
- 1e0beb45191ad8f9d85cdfec21166f58af394388edeb13a77a3edbe148b05949
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