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:
- dbbe162b8db2c6c30880ecbba4adfefb9754b69714a15ffbdda8e96547b44cdc
- Size of remote file:
- 343 MB
- SHA256:
- 5783c3d3fffcb3ea6d68211529becfad4eed28e241cad3e308ef08acb81cf1c3
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