ModelPublicadoExterno

Fastvit Mci2.apple Mclip2 Dfndr2b

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

Fuentehuggingface.co/timm/fastvit_mci2.apple_mclip2_dfndr2b/tree/91f3aaeebee061158a8f644b3e2ddac709053372

TipoOtherVersiónRevision 91f3aaeCcalidad

Fuente del modelo

Tipo: Other
Tamaño del archivo: 137–138 MB
Versión: vRevision 91f3aae
Actualizado: 16 sept 2026
Descargas: 159
Fuente: Hugging Face

Descripción de la fuente

Model card for fastvit_mci2.apple_mclip2_dfndr2b

A MobileCLIP v2 (image encoder only) for timm. Equivalent to image tower from https://huggingface.co/timm/MobileCLIP2-S2-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}
        }

Fuentes

1 fuente

Hugging FacePrincipalVersión 91f3aaeebee061158a8f644b3e2ddac709053372

huggingface.co/timm/fastvit_mci2.apple_mclip2_dfndr2b/tree/91f3aaeebee061158a8f644b3e2ddac709053372

Verificado 2 sept

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Artefactos del modelo

2 artefactos

model.safetensors

safetensors · 137 MB · SHA-256 791949bd5ef2…2671 · Hugging Face

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pytorch_model.bin

bin · 138 MB · SHA-256 c328aa273535…0505 · Hugging Face

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Extractos de fuentes

2 extractos

Readme2 septhuggingface.co/timm/fastvit_mci2.apple_mclip2_dfndr2b

--- tags: - timm - transformers - image-feature-extraction - mobileclip - mobileclip2 library_name: timm license: apple-amlr datasets: - dfndr-2b --- # Model card for fastvit_mci2.apple_mclip2_dfndr2b A MobileCLIP v2 (image encoder only) for `timm`. Equivalent to image tower from https://huggingface.co/timm/MobileCLIP2-S2-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 septhuggingface.co/timm/fastvit_mci2.apple_mclip2_dfndr2b

Source context: 159 downloads · 1 likes · Pipeline image-feature-extraction · Library timm · Repo timm/fastvit_mci2.apple_mclip2_dfndr2b