CvT-21

Wu et al., 2021 — CvT: Introducing Convolutions to Vision Transformers (arXiv:2103.15808)

Lucid port of transformers/microsoft/cvt-21, converted to Lucid-native safetensors.

Available weights

Tag acc@1 acc@5 Params GFLOPs Size Source
IN1K (default) 82.5 — 31.6M — 120.87 MB transformers

Usage

import lucid.models as models
from lucid.models.weights import CvT21Weights

# default tag
model = models.cvt_21_cls(pretrained=True)

# explicit tag (enum or string)
model = models.cvt_21_cls(weights=CvT21Weights.IN1K)
model = models.cvt_21_cls(pretrained="IN1K")

# preprocessing travels with the weights
weights = CvT21Weights.IN1K
preprocess = weights.transforms()
logits = model(preprocess(image)[None]).logits

Conversion

Converted from transformers/microsoft/cvt-21 via python -m tools.convert_weights cvt_21 --tag IN1K. Key mapping + numerical parity verified against the source.

License

apache-2.0 — inherited from the original weights.

Citation

@inproceedings{wu2021cvt,
  title={CvT: Introducing Convolutions to Vision Transformers},
  author={Wu, Haiping and Xiao, Bin and Codella, Noel and Liu, Mengchen and Dai, Xiyang and Yuan, Lu and Zhang, Lei},
  booktitle={ICCV}, year={2021}
}
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Dataset used to train lucid-dl/cvt-21

Paper for lucid-dl/cvt-21

Evaluation results