With the Masked Autoencoders' paradigm, VisionLLaMA-Large-MAE model is trained on ImageNet-1K without labels. It retains improvements over classification tasks (SFT, linear probing) on ImageNet-1K.
@article{chu2024visionllama,
title={VisionLLaMA: A Unified LLaMA Interface for Vision Tasks},
author={Chu, Xiangxiang and Su, Jianlin and Zhang, Bo and Shen, Chunhua},
journal={arXiv preprint arXiv:2403.00522},
year={2024}
}
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