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flavour
/
vtde-dinov2-small-multilingual-e5-small

Feature Extraction
Transformers
Safetensors
vision-text-dual-encoder
Model card Files Files and versions
xet
Community

Instructions to use flavour/vtde-dinov2-small-multilingual-e5-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use flavour/vtde-dinov2-small-multilingual-e5-small with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="flavour/vtde-dinov2-small-multilingual-e5-small")
    # Load model directly
    from transformers import AutoProcessor, AutoModel
    
    processor = AutoProcessor.from_pretrained("flavour/vtde-dinov2-small-multilingual-e5-small")
    model = AutoModel.from_pretrained("flavour/vtde-dinov2-small-multilingual-e5-small")
  • Notebooks
  • Google Colab
  • Kaggle
vtde-dinov2-small-multilingual-e5-small
583 MB
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  • 1 contributor
History: 3 commits
marcusinthesky's picture
marcusinthesky
Upload processor
b609404 over 2 years ago
  • .gitattributes
    1.57 kB
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  • config.json
    4.8 kB
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  • model.safetensors
    561 MB
    xet
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  • preprocessor_config.json
    491 Bytes
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  • sentencepiece.bpe.model
    5.07 MB
    xet
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  • special_tokens_map.json
    167 Bytes
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  • tokenizer.json
    17.1 MB
    xet
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  • tokenizer_config.json
    498 Bytes
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