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ildodeltaRule
/
multilingual-e5-large

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

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

  • Libraries
  • sentence-transformers

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

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("ildodeltaRule/multilingual-e5-large")
    
    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 / onnx
2.26 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 1 commit
ildodeltaRule's picture
ildodeltaRule
Added right config
2a73b22 about 2 years ago
  • config.json
    688 Bytes
    Added right config about 2 years ago
  • model.onnx
    546 kB
    xet
    Added right config about 2 years ago
  • model.onnx_data
    2.24 GB
    xet
    Added right config about 2 years ago
  • sentencepiece.bpe.model
    5.07 MB
    xet
    Added right config about 2 years ago
  • special_tokens_map.json
    280 Bytes
    Added right config about 2 years ago
  • tokenizer.json
    17.1 MB
    xet
    Added right config about 2 years ago
  • tokenizer_config.json
    418 Bytes
    Added right config about 2 years ago