Instructions to use alfredcs/vit-cifar10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alfredcs/vit-cifar10 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="alfredcs/vit-cifar10") 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("alfredcs/vit-cifar10") model = AutoModelForImageClassification.from_pretrained("alfredcs/vit-cifar10") - Notebooks
- Google Colab
- Kaggle
Init
Browse files- training_args.bin +3 -0
training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:ea673813046e88b612bbae18f24c7ca9427845086372ceaf56adb8f856bfdf28
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size 2991
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