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@@ -9,6 +9,20 @@ 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 4/255.
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  ```python
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  model, _, image_processor = open_clip.create_model_and_transforms('hf-hub:chs20/fare4-clip')
 
 
 
 
 
 
 
 
 
 
 
 
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  ```
 
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  Unsupervised adversarial fine-tuning from Openai CLIP initialization on ImageNet with infinity-norm and radius 4/255.
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+ ## Usage
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+
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  ```python
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  model, _, image_processor = open_clip.create_model_and_transforms('hf-hub:chs20/fare4-clip')
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+ ```
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+
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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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  ```