ModelPrésentéExterne

Fastvit Mci0.apple Mclip2 Dfndr2b

A MobileCLIP v2 (image encoder only) for timm. Equivalent to image tower from

Sourcehuggingface.co/timm/fastvit_mci0.apple_mclip2_dfndr2b/tree/577a2e992da2c7ba7cadc2a490bcfadfb2d69bce

TypeOtherVersionRevision 577a2e9CClasse

Source du modèle

Type: Other
Taille du fichier: 43,8–44,0 MB
Version: vRevision 577a2e9
Mis à jour: 17 sept. 2026
Téléchargements: 395
Source: Hugging Face

Description de la source

Model card for fastvit_mci0.apple_mclip2_dfndr2b

A MobileCLIP v2 (image encoder only) for timm. Equivalent to image tower from https://huggingface.co/timm/MobileCLIP2-S0-OpenCLIP.

Model Details

Dataset: DFNDR-2B
Papers:
- MobileCLIP2: Improving Multi-Modal Reinforced Training: https://arxiv.org/abs/2508.20691

Citation

@article{faghri2025mobileclip2,
          title={MobileCLIP2: Improving Multi-Modal Reinforced Training},
          author={Faghri, Fartash and Vasu, Pavan Kumar Anasosalu and Koc, Cem and Shankar, Vaishaal and Toshev, Alexander and Tuzel, Oncel and Pouransari, Hadi},
          journal={arXiv preprint arXiv:2508.20691},
          year={2025}
        }

Sources

1 source

Hugging FacePrincipalVersion 577a2e992da2c7ba7cadc2a490bcfadfb2d69bce

huggingface.co/timm/fastvit_mci0.apple_mclip2_dfndr2b/tree/577a2e992da2c7ba7cadc2a490bcfadfb2d69bce

Vérifié 2 sept.

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Artefacts du modèle

2 artefacts

model.safetensors

safetensors · 43,8 MB · SHA-256 70a995b7e738…3d04 · Hugging Face

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pytorch_model.bin

bin · 44,0 MB · SHA-256 f5be2c4f01e8…e447 · Hugging Face

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Extraits de sources

2 extraits

Readme2 sept.huggingface.co/timm/fastvit_mci0.apple_mclip2_dfndr2b

--- tags: - timm - transformers - image-feature-extraction - mobileclip - mobileclip2 library_name: timm license: apple-amlr datasets: - dfndr-2b --- # Model card for fastvit_mci0.apple_mclip2_dfndr2b A MobileCLIP v2 (image encoder only) for `timm`. Equivalent to image tower from https://huggingface.co/timm/MobileCLIP2-S0-OpenCLIP. ## Model Details - **Dataset:** DFNDR-2B - **Papers:** - MobileCLIP2: Improving Multi-Modal Reinforced Training: https://arxiv.org/abs/2508.20691 ## Citation ```bibtex @article{faghri2025mobileclip2, title={MobileCLIP2: Improving Multi-Modal Reinforced Training}, author={Faghri, Fartash and Vasu, Pavan Kumar Anasosalu and Koc, Cem and Shankar, Vaishaal and Toshev, Alexander and Tuzel, Oncel and Pouransari, Hadi}, journal={arXiv preprint arXiv:2508.20691}, year={2025} } ```

Note2 sept.huggingface.co/timm/fastvit_mci0.apple_mclip2_dfndr2b

Source context: 395 downloads · 0 likes · Pipeline image-feature-extraction · Library timm · Repo timm/fastvit_mci0.apple_mclip2_dfndr2b