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Lajavaness
/
bilingual-embedding-large

Sentence Similarity
sentence-transformers
Safetensors
Transformers
French
English
bilingual
feature-extraction
sentence-embedding
mteb
custom_code
Eval Results (legacy)
Model card Files Files and versions
xet
Community
2

Instructions to use Lajavaness/bilingual-embedding-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use Lajavaness/bilingual-embedding-large with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("Lajavaness/bilingual-embedding-large", trust_remote_code=True)
    
    sentences = [
        "C'est une personne heureuse",
        "C'est un chien heureux",
        "C'est une personne très heureuse",
        "Aujourd'hui est une journée ensoleillée"
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Transformers

    How to use Lajavaness/bilingual-embedding-large with Transformers:

    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("Lajavaness/bilingual-embedding-large", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
bilingual-embedding-large
2.26 GB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 23 commits
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dangvantuan
Update README.md
e83179d verified almost 2 years ago
  • 1_Pooling
    Initial commit almost 2 years ago
  • .gitattributes
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  • README.md
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  • config.json
    1.4 kB
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  • config_sentence_transformers.json
    176 Bytes
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  • model.safetensors
    2.24 GB
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  • modules.json
    349 Bytes
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  • sentence_bert_config.json
    53 Bytes
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  • sentencepiece.bpe.model
    5.07 MB
    xet
    Initial commit almost 2 years ago
  • special_tokens_map.json
    964 Bytes
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  • tokenizer.json
    17.1 MB
    xet
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  • tokenizer_config.json
    1.18 kB
    Initial commit almost 2 years ago