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bn22
/
vit_medium_patch28_rope_reg4_gap_224_distilled

Feature Extraction
Transformers
Safetensors
variance_pad_eva
custom_code
Model card Files Files and versions
xet
Community

Instructions to use bn22/vit_medium_patch28_rope_reg4_gap_224_distilled with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use bn22/vit_medium_patch28_rope_reg4_gap_224_distilled with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="bn22/vit_medium_patch28_rope_reg4_gap_224_distilled", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("bn22/vit_medium_patch28_rope_reg4_gap_224_distilled", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
vit_medium_patch28_rope_reg4_gap_224_distilled
238 MB
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  • 1 contributor
History: 6 commits
bn22's picture
bn22
Upload model
a55feba verified 2 days ago
  • .gitattributes
    1.52 kB
    initial commit 13 days ago
  • README.md
    5.17 kB
    Upload model 13 days ago
  • config.json
    752 Bytes
    Upload model 2 days ago
  • eva_siglip.py
    17.6 kB
    Upload model 7 days ago
  • model.safetensors
    238 MB
    xet
    Upload model 2 days ago
  • variance_pad_eva.py
    9.44 kB
    Upload model 13 days ago