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ef-zulla
/
ort-e5-small-multi-quantized

Feature Extraction
Transformers
ONNX
bert
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use ef-zulla/ort-e5-small-multi-quantized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use ef-zulla/ort-e5-small-multi-quantized with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="ef-zulla/ort-e5-small-multi-quantized")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("ef-zulla/ort-e5-small-multi-quantized")
    model = AutoModel.from_pretrained("ef-zulla/ort-e5-small-multi-quantized")
  • Notebooks
  • Google Colab
  • Kaggle
ort-e5-small-multi-quantized
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  • 1 contributor
History: 7 commits
ef-zulla's picture
ef-zulla
Upload config.json with huggingface_hub
9c690c7 over 2 years ago
  • .gitattributes
    1.57 kB
    Upload tokenizer.json with huggingface_hub over 2 years ago
  • config.json
    683 Bytes
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  • model_quantized.onnx
    118 MB
    xet
    Upload model_quantized.onnx with huggingface_hub over 2 years ago
  • sentencepiece.bpe.model
    5.07 MB
    xet
    Upload sentencepiece.bpe.model with huggingface_hub over 2 years ago
  • special_tokens_map.json
    964 Bytes
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  • tokenizer.json
    17.1 MB
    xet
    Upload tokenizer.json with huggingface_hub over 2 years ago
  • tokenizer_config.json
    1.21 kB
    Upload tokenizer_config.json with huggingface_hub over 2 years ago