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license: apache-2.0 |
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# 👁️ GLaMM-GranD-Pretrained |
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## 📝 Description |
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GLaMM-GranD-Pretrained is the model pretrained on GranD dataset, |
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a large-scale dataset generated with automated annotation pipeline for detailed region-level understanding and segmentation masks. |
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GranD comprises 7.5M unique concepts anchored in a total of 810M regions, each with a segmentation mask. |
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## 💻 Download |
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To get started with GLaMM-GranD-Pretrained, follow these steps: |
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``` |
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git lfs install |
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git clone https://huggingface.co/MBZUAI/GLaMM-GranD-Pretrained |
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``` |
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## 📚 Additional Resources |
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- **Paper:** [ArXiv](https://arxiv.org/abs/2311.03356). |
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- **GitHub Repository:** For updates: [GitHub - GLaMM](https://github.com/mbzuai-oryx/groundingLMM). |
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- **Project Page:** For a detailed overview and insights into the project, visit our [Project Page - GLaMM](https://mbzuai-oryx.github.io/groundingLMM/). |
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## 📜 Citations and Acknowledgments |
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```bibtex |
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@article{hanoona2023GLaMM, |
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title={GLaMM: Pixel Grounding Large Multimodal Model}, |
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author={Rasheed, Hanoona and Maaz, Muhammad and Shaji, Sahal and Shaker, Abdelrahman and Khan, Salman and Cholakkal, Hisham and Anwer, Rao M. and Xing, Eric and Yang, Ming-Hsuan and Khan, Fahad S.}, |
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journal={ArXiv 2311.03356}, |
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year={2023} |
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} |
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