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---
license: apache-2.0
---
<br>
# ViG Model Card
## Model Details
ViG is a generic backbone trained on the ImageNet-1K dataset for vision tasks.
- **Developed by:** [HUST](https://english.hust.edu.cn/), [Horizon Robotics](https://en.horizon.cc/)
- **Model type:** A generic vision backbone based on the Gated Linear Attention (GLA) architecture.
- **License:** Non-commercial license
### Model Sources
- **Repository:** https://github.com/hustvl/ViG
- **Paper:** https://arxiv.org/abs/2405.18425
## Uses
The primary use of ViG is research on vision tasks, e.g., classification, segmentation, detection, and instance segmentation, with an GLA-based backbone.
The primary intended users of the model are researchers and hobbyists in computer vision, machine learning, and artificial intelligence.
## Training Details
ViG is pretrained on ImageNet-1K with classification supervision.
The training data is around 1.3M images from [ImageNet-1K dataset](https://www.image-net.org/challenges/LSVRC/2012/).
See more details in this [paper](https://arxiv.org/abs/2405.18425).
## Evaluation
ViG is evaluated on ImageNet-1K val set, more details can be found in this [paper](https://arxiv.org/abs/2405.18425).
## Additional Information
## Citation Information
```
@article{vig,
title={ViG: Linear-complexity Visual Sequence Learning with Gated Linear Attention},
author={Bencheng Liao and Xinggang Wang and Lianghui Zhu and Qian Zhang and Chang Huang},
journal={arXiv preprint arXiv:2405.18425},
year={2024}
}
```
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