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--- |
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license: mit |
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library_name: open_clip |
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pipeline_tag: zero-shot-image-classification |
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--- |
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[[Paper]](https://arxiv.org/abs/2402.12336) [[GitHub]](https://github.com/chs20/RobustVLM) |
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FARE CLIP ViT-L/14 model. |
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Unsupervised adversarial fine-tuning from Openai CLIP initialization on ImageNet with infinity-norm and radius 2/255. |
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## Usage |
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```python |
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model, _, image_processor = open_clip.create_model_and_transforms('hf-hub:chs20/fare2-clip') |
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``` |
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## Citation |
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If you find this model useful, please consider citing our paper: |
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```bibtex |
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@article{schlarmann2024robustclip, |
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title={Robust CLIP: Unsupervised Adversarial Fine-Tuning of Vision Embeddings for Robust Large Vision-Language Models}, |
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author={Christian Schlarmann and Naman Deep Singh and Francesco Croce and Matthias Hein}, |
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year={2024}, |
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journal={ICML} |
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} |
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``` |
