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ComparEdge
/
saas-product-matcher

Sentence Similarity
sentence-transformers
Safetensors
English
bert
feature-extraction
saas
product-recommendation
semantic-search
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use ComparEdge/saas-product-matcher with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use ComparEdge/saas-product-matcher with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("ComparEdge/saas-product-matcher")
    
    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
saas-product-matcher
92.2 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 5 commits
ComparEdge's picture
ComparEdge
Remove hardcoded counts
b8480b4 verified 28 days ago
  • 1_Pooling
    Upload folder using huggingface_hub 28 days ago
  • .gitattributes
    1.52 kB
    initial commit 28 days ago
  • README.md
    3.59 kB
    Remove hardcoded counts 28 days ago
  • config.json
    744 Bytes
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  • config_sentence_transformers.json
    283 Bytes
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  • example_search.py
    1.47 kB
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  • model.safetensors
    90.9 MB
    xet
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  • modules.json
    429 Bytes
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  • product_embeddings.npy
    509 kB
    xet
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  • products_index.json
    67 kB
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  • sentence_bert_config.json
    241 Bytes
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  • tokenizer.json
    712 kB
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  • tokenizer_config.json
    594 Bytes
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