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LibreResNet101 Cls

ResNet-101 image classifier (224px, ImageNet-1k, 1000 classes), repackaged for LibreYOLO. 44.5M parameters.

TipoOtherVersiónRevision cf40c4bCcalidad

Fuente del modelo

Tipo
Other
Tamaño del archivo
171 MB
Versión
vRevision cf40c4b
Actualizado
17 sept 2026
Descargas
0
Fuente
Hugging Face

Descripción de la fuente

LibreResNet101-cls

ResNet-101 image classifier (224px, ImageNet-1k, 1000 classes), repackaged for LibreYOLO. ~44.5M parameters.

Source

Derived from huggingface/pytorch-image-models (timm), model resnet101.a1_in1k (the "ResNet Strikes Back" A1 recipe, ImageNet-1k). Architecture: He et al. 2015 (https://arxiv.org/abs/1512.03385). Weights by Ross Wightman and the timm contributors. Copyright (c) Ross Wightman. Licensed under the Apache License 2.0.

Modifications

Learned parameters are unchanged from timm. The checkpoint is metadata-wrapped into the LibreYOLO format (model_family / task / nc / names). LibreYOLO's native ResNet (v1.5) mirrors timm/torchvision module names, so inference is bit-identical to timm (max_abs_diff == 0, verified by the parity test). See weights/convert_resnet_weights.py in the LibreYOLO source repository.

Usage

from libreyolo import LibreYOLO

model = LibreYOLO("LibreResNet101-cls.pt")
result = model.predict("image.jpg")[0]
print(result.probs.top1, result.probs.top5)

License

Apache License 2.0. See the LICENSE and NOTICE files in this repository.

Fuentes

1 fuente
Hugging FacePrincipalVersión cf40c4bab5009980401fb0b00176f30922ada2d5
huggingface.co/LibreYOLO/LibreResNet101-cls/tree/cf40c4bab5009980401fb0b00176f30922ada2d5

Verificado 2 sept

Artefactos del modelo

1 artefacto

LibreResNet101-cls.pt

pt · 171 MB · SHA-256 188d2ebb20c7…9d62 · Hugging Face

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Extractos de fuentes

2 extractos

--- license: apache-2.0 library_name: libreyolo pipeline_tag: image-classification tags: - image-classification - resnet - imagenet - libreyolo datasets: - imagenet-1k --- # LibreResNet101-cls ResNet-101 image classifier (224px, ImageNet-1k, 1000 classes), repackaged for [LibreYOLO](https://github.com/LibreYOLO/libreyolo). ~44.5M parameters. ## Source Derived from [huggingface/pytorch-image-models (timm)](https://github.com/huggingface/pytorch-image-models), model `resnet101.a1_in1k` (the "ResNet Strikes Back" A1 recipe, ImageNet-1k). Architecture: He et al. 2015 (https://arxiv.org/abs/1512.03385). Weights by Ross Wightman and the timm contributors. Copyright (c) Ross Wightman. Licensed under the Apache License 2.0. ## Modifications Learned parameters are unchanged from timm. The checkpoint is metadata-wrapped into the LibreYOLO format (model_family / task / nc / names). LibreYOLO's native ResNet (v1.5) mirrors timm/torchvision module names, so inference is bit-identical to timm (max_abs_diff == 0, verified by the parity test). See `weights/convert_resnet_weights.py` in the [LibreYOLO source repository](https://github.com/LibreYOLO/libreyolo). ## Usage ```python from libreyolo import LibreYOLO model = LibreYOLO("LibreResNet101-cls.pt") result = model.predict("image.jpg")[0] print(result.probs.top1, result.probs.top5) ``` ## License Apache License 2.0. See the [`LICENSE`](./LICENSE) and [`NOTICE`](./NOTICE) files in this repository.

Source context: 0 downloads · 0 likes · Pipeline image-classification · Library libreyolo · Repo LibreYOLO/LibreResNet101-cls