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DeKUT-DSAIL/convnextv2-huge-cifar10-native
convnextv2-huge-cifar10-native is a image classification model from DeKUT-DSAIL. Use it when you need a label for an image. It is set up for timm. The card lists the license as mit.
ConvNeXt V2 Huge fine-tuned on CIFAR-10 at native 32x32 resolution (adapted stem).
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From the Hugging Face model README
ConvNeXt V2 Huge fine-tuned on CIFAR-10 at native 32x32 resolution (adapted stem).
Fine-tuned from ImageNet-pretrained weights (timm name convnextv2_huge) on
CIFAR-10 as part of a native-resolution vs upsampling study.
| Metric | Value |
|---|---|
| Top-1 accuracy | 99.18% |
| Top-5 accuracy | 99.91% |
| F1 (macro) | 0.9918 |
| AUC (macro) | 0.9991 |
| ECE | 0.1082 |
[0.4914, 0.4822, 0.4465] and std [0.247, 0.2435, 0.2616].from cifar_classifier import CIFAR10Classifier
clf = CIFAR10Classifier.from_pretrained("DeKUT-DSAIL/convnextv2-huge-cifar10-upsample")
label, probs = clf.predict("image.jpg")
print(label, probs)
airplane, automobile, bird, cat, deer, dog, frog, horse, ship, truck