cvt-13

CvT-13

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

Lucid port of transformers/microsoft/cvt-13, converted to Lucid-native safetensors.

Available weights

Usage

import lucid.models as models
from lucid.models.weights import CvT13Weights

# default tag
model = models.cvt_13_cls(pretrained=True)

# explicit tag (enum or string)
model = models.cvt_13_cls(weights=CvT13Weights.IN1K)
model = models.cvt_13_cls(pretrained="IN1K")

# preprocessing travels with the weights
weights = CvT13Weights.IN1K
preprocess = weights.transforms()
logits = model(preprocess(image)[None]).logits

Conversion

Converted from transformers/microsoft/cvt-13 via python -m tools.convert_weights cvt_13 --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}
}