Instructions to use ArSenic04/Sports_Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ArSenic04/Sports_Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ArSenic04/Sports_Classification") 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("ArSenic04/Sports_Classification") model = AutoModelForImageClassification.from_pretrained("ArSenic04/Sports_Classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7821a715b8dad87169641a578a4a961c8fd78f872b5fadf74ece766915aa1c5e
- Size of remote file:
- 343 MB
- SHA256:
- a647f8e69db76a4678f14201bd5c7509d05286185cd0836c90b181d32db2e80a
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