Push model using huggingface_hub.
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README.md
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---
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library_name: XTransferBench
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license: mit
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pipeline_tag: zero-shot-classification
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tags:
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- not-for-all-audiences
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- pytorch_model_hub_mixin
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- model_hub_mixin
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---
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</div>
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Pre-trained UAP/TUAP for ICML2025 paper ["X-Transfer Attacks: Towards Super Transferable Adversarial Attacks on CLIP"](https://openreview.net/forum?id=KmQEsIfhr9)
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---
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## X-TransferBench
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X-TransferBench is an open-source benchmark that provides a comprehensive collection of UAPs/TUAPs capable of achieving universal adversarial transferability. These UAPs can simultaneously **transfer across data, domains, models**, and **tasks**. Essentially, they represent perturbations that can transform any sample into an adversarial example, effective against any model and for any task.
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## Model Details
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- Surrogate Model Search Space: Base
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- Surrogate Dataset: ImageNet
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- Threat Model: L_inf_eps=12/255
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- Perturbation Size: 3 x 224 x 224
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---
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## Model Usage
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```python
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from XTransferBench import attacker
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attacker = XTransferBench.zoo.load_attacker("linf_non_targeted", "xtransfer_base_linf_eps12_non_targeted")
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attacker = attacker.to(device)
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images = # torch.Tensor [b, 3, h, w], values should be between 0 and 1
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adv_images = attacker(images) # adversarial examples
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```
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---
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## Citation
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If you use this model in your work, please cite the accompanying paper:
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```
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@inproceedings{
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huang2025xtransfer,
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title={X-Transfer Attacks: Towards Super Transferable Adversarial Attacks on CLIP},
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author={Hanxun Huang and Sarah Erfani and Yige Li and Xingjun Ma and James Bailey},
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booktitle={ICML},
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year={2025},
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}
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```
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---
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library_name: XTransferBench
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tags:
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- model_hub_mixin
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- pytorch_model_hub_mixin
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This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration:
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- Code: [More Information Needed]
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- Paper: [More Information Needed]
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- Docs: [More Information Needed]
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config.json
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{
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"checkpoint_path":
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"epsilon": 0.047058823529411764,
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"image_size": 224
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}
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{
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"checkpoint_path": "/data/gpfs/projects/punim0784/hanxunh/clip_uap_transfer_dev/experiments/untargeted/in1k/base/mab_ucb_rho2/Ensemble4/l_inf_pgd_12/checkpoints/delta.pth",
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"epsilon": 0.047058823529411764,
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"image_size": 224
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}
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