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texonom
/
multilingual-e5-small-4096

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

Instructions to use texonom/multilingual-e5-small-4096 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use texonom/multilingual-e5-small-4096 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="texonom/multilingual-e5-small-4096", trust_remote_code=True)
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("texonom/multilingual-e5-small-4096", trust_remote_code=True)
    model = AutoModel.from_pretrained("texonom/multilingual-e5-small-4096", trust_remote_code=True)
  • Notebooks
  • Google Colab
  • Kaggle
multilingual-e5-small-4096
137 MB
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  • 1 contributor
History: 4 commits
seonglae's picture
seonglae
Delete onnx/model.onnx
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  • onnx
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  • .gitattributes
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  • README.md
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  • config.json
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  • quantize_config.json
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  • special_tokens_map.json
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  • tokenizer.json
    17.1 MB
    xet
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  • tokenizer_config.json
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