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lucid-dl/mobilenet-v3-small
mobilenet-v3-small is a image classification model from lucid-dl. Use it when you need a label for an image. It is set up for lucid. The card lists the license as bsd-3-clause.
Howard et al., 2019 — Searching for MobileNetV3 (arXiv:1905.02244)
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Updated May 29, 2026
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From the Hugging Face model README
Howard et al., 2019 — Searching for MobileNetV3 (arXiv:1905.02244)
Lucid port of torchvision/MobileNet_V3_Small_Weights.IMAGENET1K_V1,
converted to Lucid-native safetensors.
| Tag | acc@1 | acc@5 | Params | GFLOPs | Size | Source |
|---|---|---|---|---|---|---|
IMAGENET1K_V1 (default) | 67.668 | 87.402 | 2.5M | 0.057 | 9.77 MB | torchvision |
import lucid.models as models
from lucid.models.weights import MobileNetV3SmallWeights
# default tag
model = models.mobilenet_v3_small_cls(pretrained=True)
# explicit tag (enum or string)
model = models.mobilenet_v3_small_cls(weights=MobileNetV3SmallWeights.IMAGENET1K_V1)
model = models.mobilenet_v3_small_cls(pretrained="IMAGENET1K_V1")
# preprocessing travels with the weights
weights = MobileNetV3SmallWeights.IMAGENET1K_V1
preprocess = weights.transforms()
logits = model(preprocess(image)[None]).logits
Converted from torchvision/MobileNet_V3_Small_Weights.IMAGENET1K_V1 via
python -m tools.convert_weights mobilenet_v3_small --tag IMAGENET1K_V1.
Key mapping + numerical parity verified against the source.
bsd-3-clause — inherited from the original weights.
@inproceedings{howard2019searching,
title={Searching for MobileNetV3},
author={Howard, Andrew and Sandler, Mark and Chu, Grace and Chen, Liang-Chieh and Chen, Bo and Tan, Mingxing and Wang, Weijun and Zhu, Yukun and Pang, Ruoming and Vasudevan, Vijay and others},
booktitle={ICCV}, year={2019}
}