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--- |
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license: apache-2.0 |
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tags: |
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- self-supervised learning |
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- vision |
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- GMML |
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inference: false |
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--- |
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# Model description |
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GMML is a self-supervised learning model that learns to group masked pixels in an image. The model is trained on ImageNet-1K. |
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# Model Sources |
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- https://github.com/Sara-Ahmed/GMML |
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- https://arxiv.org/abs/2205.14986 |
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# Model Card Authors |
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Sara Atito, Muhammad Awais, Josef Kittler |
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# How to use |
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```python |
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from transformers import BertConfig, BertModel |
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config = BertConfig() |
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model = BertModel(config) |
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model.push_to_hub("nielsr/my-awesome-bert-model") |
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# reload |
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model = BertModel.from_pretrained("nielsr/my-awesome-bert-model") |
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``` |
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# BibTeX entry and citation info |
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``` |
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@inproceedings{atito2023gmml, |
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title={GMML is all you need}, |
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author={Atito, Sara and Awais, Muhammed and Nandam, Srinivasa and Kittler, Josef}, |
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booktitle={2023 IEEE International Conference on Image Processing (ICIP)}, |
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pages={2125--2129}, |
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year={2023}, |
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organization={IEEE} |
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} |
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``` |