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nixiesearch
/
all-MiniLM-L6-v2-onnx

Feature Extraction
sentence-transformers
ONNX
English
bert
sentence-similarity
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use nixiesearch/all-MiniLM-L6-v2-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use nixiesearch/all-MiniLM-L6-v2-onnx with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("nixiesearch/all-MiniLM-L6-v2-onnx")
    
    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
all-MiniLM-L6-v2-onnx
114 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
shuttie's picture
shuttie
add quantized version
1e6ba95 over 2 years ago
  • .gitattributes
    139 Bytes
    initial commit almost 3 years ago
  • README.md
    801 Bytes
    add readme almost 3 years ago
  • config.json
    650 Bytes
    initial commit almost 3 years ago
  • model.onnx
    90.4 MB
    xet
    initial commit almost 3 years ago
  • model_quantized.onnx
    23 MB
    xet
    add quantized version over 2 years ago
  • quantize_config.json
    674 Bytes
    add quantized version over 2 years ago
  • special_tokens_map.json
    125 Bytes
    initial commit almost 3 years ago
  • tokenizer.json
    712 kB
    xet
    initial commit almost 3 years ago
  • tokenizer_config.json
    366 Bytes
    initial commit almost 3 years ago
  • vocab.txt
    232 kB
    xet
    initial commit almost 3 years ago