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Xie et al., 2017 — Aggregated Residual Transformations for Deep Neural Networks (arXiv:1611.05431)
timm/resnext101_32x4d.gluon_in1k,
converted to Lucid-native safetensors.| Tag | acc@1 | acc@5 | Params | GFLOPs | Size | Source |
|---|---|---|---|---|---|---|
GLUON_IN1K (default) | 80.342 | 94.926 | 44.2M | — | 169.11 MB | timm |
1import lucid.models as models
2from lucid.models.weights import ResNeXt101_32x4dWeights
3
4# default tag
5model = models.resnext_101_32x4d_cls(pretrained=True)
6
7# explicit tag (enum or string)
8model = models.resnext_101_32x4d_cls(weights=ResNeXt101_32x4dWeights.GLUON_IN1K)
9model = models.resnext_101_32x4d_cls(pretrained="GLUON_IN1K")
10
11# preprocessing travels with the weights
12weights = ResNeXt101_32x4dWeights.GLUON_IN1K
13preprocess = weights.transforms()
14logits = model(preprocess(image)[None]).logitstimm/resnext101_32x4d.gluon_in1k via
python -m tools.convert_weights resnext_101_32x4d --tag GLUON_IN1K.
Key mapping + numerical parity verified against the source.apache-2.0 — inherited from the original weights.@inproceedings{xie2017aggregated,
title={Aggregated Residual Transformations for Deep Neural Networks},
author={Xie, Saining and Girshick, Ross and Doll{\'a}r, Piotr and Tu, Zhuowen and He, Kaiming},
booktitle={CVPR}, year={2017}
}