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texonom
/
e5-base-multilingual-4096

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

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

  • Libraries
  • Transformers

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

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="texonom/e5-base-multilingual-4096", trust_remote_code=True)
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("texonom/e5-base-multilingual-4096", trust_remote_code=True)
    model = AutoModel.from_pretrained("texonom/e5-base-multilingual-4096", trust_remote_code=True)
  • Notebooks
  • Google Colab
  • Kaggle
e5-base-multilingual-4096
1.42 GB
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  • 1 contributor
History: 3 commits
seonglae's picture
seonglae
Create README.md
c96727e over 2 years ago
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  • .gitattributes
    1.57 kB
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  • README.md
    74 Bytes
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  • config.json
    1.66 kB
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  • quantize_config.json
    834 Bytes
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  • special_tokens_map.json
    280 Bytes
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  • tokenizer.json
    17.1 MB
    xet
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  • tokenizer_config.json
    609 Bytes
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