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Slep
/
CondViT-B16-txt

Feature Extraction
Transformers
Safetensors
condvit
lrvsf-benchmark
custom_code
Eval Results (legacy)
Model card Files Files and versions
xet
Community

Instructions to use Slep/CondViT-B16-txt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Slep/CondViT-B16-txt with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="Slep/CondViT-B16-txt", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("Slep/CondViT-B16-txt", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
CondViT-B16-txt
5.31 GB
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  • 1 contributor
History: 9 commits
Slep's picture
Slep
Update README.md
5ee6619 verified almost 2 years ago
  • .gitattributes
    1.52 kB
    initial commit about 2 years ago
  • README.md
    3.96 kB
    Update README.md almost 2 years ago
  • config.json
    568 Bytes
    Upload CondViTForEmbedding about 2 years ago
  • hf_model.py
    2.03 kB
    Remove hardcoded move to device in forward. about 2 years ago
  • model-00001-of-00002.safetensors
    4.97 GB
    xet
    Upload CondViTForEmbedding about 2 years ago
  • model-00002-of-00002.safetensors
    339 MB
    xet
    Upload CondViTForEmbedding about 2 years ago
  • model.safetensors.index.json
    34.5 kB
    Upload CondViTForEmbedding about 2 years ago
  • module.py
    4.58 kB
    Upload CondViTForEmbedding about 2 years ago
  • preprocessor_config.json
    361 Bytes
    Upload processor about 2 years ago
  • processor.py
    2.19 kB
    Optional texts in processor. about 2 years ago