README.md

metadata

license: apache-2.0
datasets:
  - imagenet-1k
metrics:
  - accuracy
pipeline_tag: image-classification

VisionLLaMA-Base-MAE

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.

Model	ImageNet Acc (SFT)	ImageNet Acc (Linear Probe)
VisionLLaMA-Large-MAE (ep800)	85.5	77.3

How to Use

Please refer the Github page for usage.

Citation

@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}
}