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Viyog Weights

Finetuned classification checkpoints used in Viyog (separating adversarial from out-of-distribution inputs). 20 architectures (ResNet/DenseNet/ConvNeXt/Swin/ViT edge backbones) across CIFAR-100, CIFAR-10, GTSRB.

TipoOtherVersiónConvnextv2 baseCcalidad

Fuente del modelo

Tipo
Other
Tamaño del archivo
13,6–655 MB
Versión
vConvnextv2 base
Actualizado
22 oct 2026
Fuente
Hugging Face

Descripción de la fuente

Viyog — finetuned backbones

Finetuned classification checkpoints used in Viyog (separating adversarial from out-of-distribution inputs). 20 architectures (ResNet/DenseNet/ConvNeXt/Swin/ViT

  • edge backbones) across CIFAR-100, CIFAR-10, GTSRB.

Layout — state_dict .pth files:

  • root: the 4 original CIFAR-100 backbones (convnextv2_base, swin_tiny, vit_b, tf_efficientnetv2_l)
  • cifar100/, cifar10/, gtsrb/: per-dataset checkpoints for every architecture

Package: pip install viyog · code: https://github.com/amanyagami/viyog · demo: https://huggingface.co/spaces/amanyagami/viyog

Fuentes

1 fuente
Hugging FacePrincipalVersión b96263ae28a8585acaad6a002a0298b6b6c2d735
huggingface.co/amanyagami/viyog-weights/tree/b96263ae28a8585acaad6a002a0298b6b6c2d735

Verificado 22 oct

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Artefactos del modelo

34 artefactos

cifar10/convnextv2_base.pth

pth · 335 MB · SHA-256 8f43015c2523…fcf6 · Hugging Face

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cifar10/densenet121.pth

pth · 27,1 MB · SHA-256 336eaa8ced6e…888d · Hugging Face

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cifar10/mobilenetv3_l.pth

pth · 16,3 MB · SHA-256 956925c956af…428a · Hugging Face

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cifar10/resnet18.pth

pth · 42,7 MB · SHA-256 ff38f7dcd880…0b4f · Hugging Face

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cifar10/resnet34.pth

pth · 81,3 MB · SHA-256 e0f15c29976d…e082 · Hugging Face

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cifar10/resnet50.pth

pth · 90,0 MB · SHA-256 151836a434c1…a340 · Hugging Face

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cifar10/swin_tiny.pth

pth · 105 MB · SHA-256 7765bd9b79db…a010 · Hugging Face

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cifar10/vit_base.pth

pth · 327 MB · SHA-256 f090bcc606d8…fd81 · Hugging Face

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cifar100/densenet121.pth

pth · 27,5 MB · SHA-256 ebb793c0add7…361f · Hugging Face

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cifar100/densenet161.pth

pth · 103 MB · SHA-256 7edc5a11dd0f…09eb · Hugging Face

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cifar100/densenet169.pth

pth · 49,2 MB · SHA-256 ee19f5f6b58b…d583 · Hugging Face

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cifar100/densenet201.pth

pth · 71,0 MB · SHA-256 c5130782f022…e45a · Hugging Face

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cifar100/edgenext_small.pth

pth · 20,3 MB · SHA-256 2b713bef1200…0bb7 · Hugging Face

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cifar100/efficientvit_b1.pth

pth · 29,4 MB · SHA-256 570ad59eccd5…cc17 · Hugging Face

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cifar100/effnet_lite0.pth

pth · 13,6 MB · SHA-256 53352b3b8947…eee4 · Hugging Face

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cifar100/fastvit_sa12.pth

pth · 41,0 MB · SHA-256 eac647f4ef15…6a21 · Hugging Face

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cifar100/mobilenetv3_l.pth

pth · 16,7 MB · SHA-256 11c01bbb5b0d…d697 · Hugging Face

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cifar100/mobilenetv4_m.pth

pth · 33,1 MB · SHA-256 60ff4bb03f00…edcb · Hugging Face

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cifar100/mobileone_s1.pth

pth · 14,4 MB · SHA-256 3a31399b4b40…1dd8 · Hugging Face

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cifar100/resnet101.pth

pth · 163 MB · SHA-256 4437494670b5…b1c1 · Hugging Face

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cifar100/resnet152.pth

pth · 223 MB · SHA-256 120b8c39196c…a4eb · Hugging Face

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cifar100/resnet18.pth

pth · 42,9 MB · SHA-256 16fae195973e…7a38 · Hugging Face

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cifar100/resnet34.pth

pth · 81,5 MB · SHA-256 7ac3b17b7eee…bd9f · Hugging Face

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cifar100/resnet50.pth

pth · 90,8 MB · SHA-256 bc40ed9e6005…3423 · Hugging Face

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convnextv2_base_cifar100.pth

pth · 655 MB · SHA-256 db9fa05b4365…5988 · Hugging Face

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gtsrb/convnextv2_base.pth

pth · 335 MB · SHA-256 d47e5503a05e…f045 · Hugging Face

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gtsrb/densenet121.pth

pth · 27,2 MB · SHA-256 712374145867…e247 · Hugging Face

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gtsrb/mobilenetv3_l.pth

pth · 16,4 MB · SHA-256 479d90e528d0…0fca · Hugging Face

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gtsrb/resnet50.pth

pth · 90,3 MB · SHA-256 0212497137a7…2833 · Hugging Face

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gtsrb/swin_tiny.pth

pth · 105 MB · SHA-256 36da7a27aa92…b585 · Hugging Face

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gtsrb/vit_base.pth

pth · 327 MB · SHA-256 d733d4a6bd4f…24b9 · Hugging Face

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swin_tiny_patch4_window7_224_cifar100.pth

pth · 172 MB · SHA-256 a843101bed5c…0e81 · Hugging Face

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tf_efficientnetv2_l_cifar100.pth

pth · 454 MB · SHA-256 0cf62a4041db…9f1d · Hugging Face

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vit_b_cifar100.pth

pth · 544 MB · SHA-256 5635e650bfde…8f23 · Hugging Face

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Extractos de fuentes

2 extractos

--- license: mit library_name: timm tags: - image-classification - adversarial-robustness - ood-detection - viyog --- # Viyog — finetuned backbones Finetuned classification checkpoints used in **Viyog** (separating adversarial from out-of-distribution inputs). 20 architectures (ResNet/DenseNet/ConvNeXt/Swin/ViT + edge backbones) across **CIFAR-100, CIFAR-10, GTSRB**. **Layout** — `state_dict` `.pth` files: - root: the 4 original CIFAR-100 backbones (convnextv2_base, swin_tiny, vit_b, tf_efficientnetv2_l) - `cifar100/`, `cifar10/`, `gtsrb/`: per-dataset checkpoints for every architecture Package: `pip install viyog` · code: https://github.com/amanyagami/viyog · demo: https://huggingface.co/spaces/amanyagami/viyog

Source context: 0 downloads · 0 likes · Pipeline image-classification · Library timm · Repo amanyagami/viyog-weights