标签:

• timm
• transformers
• 图像特征提取
• siglip
• siglip2 库名称: timm 许可证: apache-2.0 数据集:
• webli

模型卡片 vit_large_patch16_siglip_gap_256.v2_webli

一个专为timm设计的SigLIP 2 ViT（仅图像编码器）。等效于来自https://huggingface.co/timm/ViT-L-16-SigLIP2-256的图像塔。此gap变体采用全局平均池化，并移除了注意力池化头。

模型详情

• 数据集: webli
• 论文:
  • SigLIP 2: 具有改进的语义理解、定位和密集特征的多语言视觉-语言编码器: https://arxiv.org/abs/2502.14786
  • 用于语言图像预训练的Sigmoid损失: https://arxiv.org/abs/2303.15343

引用

@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}
        }