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towing
/
gte-small-zh

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

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

  • Libraries
  • sentence-transformers

    How to use towing/gte-small-zh with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("towing/gte-small-zh")
    
    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-small-zh
151 MB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 5 commits
towing's picture
towing
Update README.md
1c3bfeb verified about 2 years ago
  • onnx
    add quantized onnx modal about 2 years ago
  • .gitattributes
    1.52 kB
    initial commit about 2 years ago
  • README.md
    32.9 kB
    Update README.md about 2 years ago
  • config.json
    788 Bytes
    add quantized onnx modal about 2 years ago
  • quantize_config.json
    674 Bytes
    add quantized onnx modal about 2 years ago
  • special_tokens_map.json
    695 Bytes
    add quantized onnx modal about 2 years ago
  • tokenizer.json
    298 kB
    add quantized onnx modal about 2 years ago
  • tokenizer_config.json
    1.49 kB
    add quantized onnx modal about 2 years ago
  • vocab.txt
    70 kB
    add quantized onnx modal about 2 years ago