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NoesisLab
/
Collins-Embedding-3M

Sentence Similarity
sentence-transformers
Safetensors
English
feature-extraction
Model card Files Files and versions
xet
Community

Instructions to use NoesisLab/Collins-Embedding-3M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use NoesisLab/Collins-Embedding-3M with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("NoesisLab/Collins-Embedding-3M")
    
    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
Collins-Embedding-3M / 0_CollinsSTWrapper
13.5 MB
Ctrl+K
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  • 1 contributor
History: 2 commits
OzTianlu's picture
OzTianlu
Upload modeling_hf.py
dc694a3 verified about 2 months ago
  • config.json
    406 Bytes
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  • model.safetensors
    12.5 MB
    xet
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  • modeling_hf.py
    7.97 kB
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  • special_tokens_map.json
    125 Bytes
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  • tokenizer.json
    712 kB
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  • tokenizer_config.json
    1.22 kB
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  • vocab.txt
    232 kB
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