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README.md

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-license: mit
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+license: apache-2.0
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+<br>
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+# GroupMamba-Small Model Card
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+## Model Details
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+GroupMamba-Small is a generic backbone with 34M parameters trained on the ImageNet-1K dataset for vision tasks.
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+- **Model type:** Parameter-Efficient and Accurate Vision Backbone Based on Group Visual State Space Model
+- **License:** Non-commercial license
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+### Model Sources
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+- **Repository:** https://github.com/amshaker/GroupMamba
+- **Paper:** https://arxiv.org/abs/X.X
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+## Uses
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+The primary use of GroupMamba is research on vision tasks, e.g., classification, segmentation, detection, and instance segmentation, with an SSM-based backbone.
+The primary intended users of the model are researchers and hobbyists in computer vision, machine learning, and artificial intelligence.
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+## How to Get Started with the Model
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+- You can replace the backbone for vision tasks with the proposed GroupMamba: https://github.com/Amshaker/GroupMamba/blob/main/classification/models/groupmamba.py
+- Then you can load this checkpoint and start fine-tuning.
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+## Training Details
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+GroupMamba 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/X.X.
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+## Evaluation
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+GroupMamba-Small is evaluated on ImageNet-1K val set, and achieves 83.9% Top-1 Acc with only 34M parameters. See more details in this [paper](https://arxiv.org/abs/X.X).
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+## Additional Information
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+### Citation Information
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+```
+@article{GroupMamba,
+  title={GroupMamba: Parameter-Efficient and Accurate Group Visual State Space Model},
+  author={Abdelrahman Shaker and Syed Talal Wasim and Salman Khan and Gall Jürgen and Fahad Khan},
+  journal={arXiv preprint arXiv:X.X},
+  year={2024}
+}
+```
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+