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
# Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification
processor = AutoImageProcessor.from_pretrained("ArSenic04/Sports_Classification")
model = AutoModelForImageClassification.from_pretrained("ArSenic04/Sports_Classification")Quick Links
Sports_Classification
Autogenerated by HuggingPics🤗🖼️
Create your own image classifier for anything by running the demo on Google Colab.
Report any issues with the demo at the github repo.
Example Images
baseball
cricket ball
football
tennisball
volleyball
- Downloads last month
- 25
Evaluation results
- Accuracyself-reported0.832





# 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")