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morgendigital
/
multilingual-e5-large-quantized

Feature Extraction
sentence-transformers
ONNX
xlm-roberta
mteb
Sentence Transformers
sentence-similarity
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community
1

Instructions to use morgendigital/multilingual-e5-large-quantized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use morgendigital/multilingual-e5-large-quantized with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("morgendigital/multilingual-e5-large-quantized")
    
    sentences = [
        "The weather is lovely today.",
        "It's so sunny outside!",
        "He drove to the stadium."
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [3, 3]
  • Notebooks
  • Google Colab
  • Kaggle
multilingual-e5-large-quantized
2.82 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 6 commits
freefallr's picture
freefallr
Update README.md
1d1b43d over 2 years ago
  • onnx
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  • .gitattributes
    1.63 kB
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  • README.md
    160 kB
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  • config.json
    688 Bytes
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  • quantize_config.json
    834 Bytes
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  • sentencepiece.bpe.model
    5.07 MB
    xet
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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
    418 Bytes
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