Instructions to use hiendang7613/test-cifar-10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hiendang7613/test-cifar-10 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hiendang7613/test-cifar-10") 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("hiendang7613/test-cifar-10") model = AutoModelForImageClassification.from_pretrained("hiendang7613/test-cifar-10") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7c3d1dbe0dfabd733d98979b3c6c3771866ae1c6ebec68c0627e3d12e6753204
- Size of remote file:
- 4.54 kB
- SHA256:
- 199cb3f5e6097eb45f9b89a34052a7a92d02409f6f342db434225e844973cf97
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