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vectoriseai
/
gte-base

Sentence Similarity
sentence-transformers
PyTorch
ONNX
English
bert
mteb
Sentence Transformers
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community
1

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

  • Libraries
  • sentence-transformers

    How to use vectoriseai/gte-base with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("vectoriseai/gte-base")
    
    sentences = [
        "That is a happy person",
        "That is a happy dog",
        "That is a very happy person",
        "Today is a sunny day"
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
gte-base / onnx
546 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 1 commit
nanmoon's picture
nanmoon
gte-base
b9fd30d over 2 years ago
  • model.onnx
    436 MB
    xet
    gte-base over 2 years ago
  • model_quantized.onnx
    110 MB
    xet
    gte-base over 2 years ago