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metarank
/
multilingual-e5-small

Feature Extraction
sentence-transformers
ONNX
English
bert
sentence-similarity
text-embeddings-inference
Model card Files Files and versions
xet
Community

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

  • Libraries
  • sentence-transformers

    How to use metarank/multilingual-e5-small with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("metarank/multilingual-e5-small")
    
    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-small
492 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 1 commit
shuttie's picture
shuttie
initial commit
ec841bb over 2 years ago
  • .gitattributes
    138 Bytes
    initial commit over 2 years ago
  • README.md
    1.22 kB
    initial commit over 2 years ago
  • config.json
    653 Bytes
    initial commit over 2 years ago
  • pytorch_model.onnx
    470 MB
    xet
    initial commit over 2 years ago
  • sentencepiece.bpe.model
    5.07 MB
    xet
    initial commit over 2 years ago
  • special_tokens_map.json
    167 Bytes
    initial commit over 2 years ago
  • tokenizer.json
    17.1 MB
    xet
    initial commit over 2 years ago
  • tokenizer_config.json
    443 Bytes
    initial commit over 2 years ago