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Alibaba-NLP
/
gte-multilingual-base

Sentence Similarity
sentence-transformers
Safetensors
Transformers
new
feature-extraction
mteb
multilingual
text-embeddings-inference
custom_code
Eval Results (legacy)
Model card Files Files and versions
xet
Community
30

Instructions to use Alibaba-NLP/gte-multilingual-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use Alibaba-NLP/gte-multilingual-base with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("Alibaba-NLP/gte-multilingual-base", trust_remote_code=True)
    
    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]
  • Transformers

    How to use Alibaba-NLP/gte-multilingual-base with Transformers:

    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("Alibaba-NLP/gte-multilingual-base", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
gte-multilingual-base
630 MB
Ctrl+K
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  • 8 contributors
History: 23 commits
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michaelfeil
Update README.md
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