Aller au contenu
ModelPrésentéExterne
Télécharger

Vit So400m Patch14 Siglip 378.v2 Webli

A SigLIP 2 ViT (image encoder only) for timm. Equivalent to image tower from

TypeOtherVersionRevision 089d92c

Source du modèle

Type
Other
Taille du fichier
1,60 GB
Version
vRevision 089d92c
Mis à jour
28 sept. 2026
Téléchargements
616
Source
Hugging Face

Description de la source

Model card for vit_so400m_patch14_siglip_378.v2_webli

A SigLIP 2 ViT (image encoder only) for timm. Equivalent to image tower from https://huggingface.co/timm/ViT-SO400M-14-SigLIP2-378.

Model Details

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}
        }
        

Sources

1 source
Hugging FacePrincipalVersion 089d92c25ac75658b36885acb4b8ebb954b35ed3
huggingface.co/timm/vit_so400m_patch14_siglip_378.v2_webli/tree/089d92c25ac75658b36885acb4b8ebb954b35ed3

Vérifié 28 sept.

Artefacts du modèle

2 artefacts

model.safetensors

safetensors · 1,60 GB · SHA-256 03e8de52efb0…a83f · Hugging Face

Télécharger

pytorch_model.bin

bin · 1,60 GB · SHA-256 889bfb711a0e…9c67 · Hugging Face

Télécharger

Extraits de sources

2 extraits

--- tags: - timm - transformers - image-feature-extraction - siglip - siglip2 library_name: timm license: apache-2.0 datasets: - webli --- # Model card for vit_so400m_patch14_siglip_378.v2_webli A SigLIP 2 ViT (image encoder only) for `timm`. Equivalent to image tower from https://huggingface.co/timm/ViT-SO400M-14-SigLIP2-378. ## Model Details - **Dataset:** webli - **Papers:** - SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features: https://arxiv.org/abs/2502.14786 - Sigmoid Loss for Language Image Pre-Training: https://arxiv.org/abs/2303.15343 ## Citation ```bibtex @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} } ``` ```bibtex @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} } ```

Source context: 616 downloads · 0 likes · Pipeline image-feature-extraction · Library timm · Repo timm/vit_so400m_patch14_siglip_378.v2_webli