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sentence-transformers
/
msmarco-bert-co-condensor

Sentence Similarity
sentence-transformers
PyTorch
ONNX
Safetensors
OpenVINO
Transformers
bert
feature-extraction
text-embeddings-inference
Model card Files Files and versions
xet
Community
2

Instructions to use sentence-transformers/msmarco-bert-co-condensor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use sentence-transformers/msmarco-bert-co-condensor with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("sentence-transformers/msmarco-bert-co-condensor")
    
    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]
  • Transformers

    How to use sentence-transformers/msmarco-bert-co-condensor with Transformers:

    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("sentence-transformers/msmarco-bert-co-condensor")
    model = AutoModel.from_pretrained("sentence-transformers/msmarco-bert-co-condensor")
  • Notebooks
  • Google Colab
  • Kaggle
msmarco-bert-co-condensor / 1_Pooling
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  • 2 contributors
History: 1 commit
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nreimers
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294fb16 over 4 years ago
  • config.json
    191 Bytes
    upload over 4 years ago