Vit Base Patch16 Siglip Gap 384.v2 Webli

🚀 vit_base_patch16_siglip_gap_384.v2_webli模型卡片

这是一个适用于timm的SigLIP 2 ViT（仅图像编码器），等同于来自https://huggingface.co/timm/ViT-B-16-SigLIP2-384的图像塔。此gap变体使用全局平均池化，并移除了注意力池化头。

🚀 快速开始

本模型是专为timm库设计的SigLIP 2 ViT图像编码器，可用于图像特征提取等任务。它与https://huggingface.co/timm/ViT-B-16-SigLIP2-384的图像塔等效，且gap变体在结构上进行了优化，移除了注意力池化头并采用全局平均池化。

📚 详细文档

模型详情

引用信息

@article{tschannen2025siglip,
          title={SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features},
          author={Tschannen, Michael and Gritsenko, Alexey and Wang, Xiao and Naeem, Muhammad Ferjad and Alabdulmohsin, Ibrahim and Parthasarathy, Nikhil and Evans, Talfan and Beyer, Lucas and Xia, Ye and Mustafa, Basil and H'enaff, Olivier and Harmsen, Jeremiah and Steiner, Andreas and Zhai, Xiaohua},
          year={2025},
          journal={arXiv preprint arXiv:2502.14786}
        }
        

@inproceedings{zhai2023sigmoid,
          title={Sigmoid loss for language image pre-training},
          author={Zhai, Xiaohua and Mustafa, Basil and Kolesnikov, Alexander and Beyer, Lucas},
          booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
          pages={11975--11986},
          year={2023}
        }
        

📄 许可证

本项目采用Apache-2.0许可证。