Vit Base Patch32 Siglip 256.v2 Webli

🚀 Model card for vit_base_patch32_siglip_256.v2_webli

A SigLIP 2 ViT (image encoder only) for timm, equivalent to the image tower from https://huggingface.co/timm/ViT-B-32-SigLIP2-256.

🚀 Quick Start

This is a SigLIP 2 ViT model designed for timm, which serves as an image encoder and is equivalent to the image tower from the specified Hugging Face model.

✨ Features

• Image Feature Extraction: Ideal for extracting features from images.
• Based on SigLIP 2: Incorporates the advancements of SigLIP 2 for better performance.

📚 Documentation

Model Details

📄 License

This model is licensed under the Apache-2.0 license.

📄 Citation

@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}
        }