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Mass-14
/
MNLP_M3_document_encoder

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

Instructions to use Mass-14/MNLP_M3_document_encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use Mass-14/MNLP_M3_document_encoder with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("Mass-14/MNLP_M3_document_encoder")
    
    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
MNLP_M3_document_encoder / openvino
1.68 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 1 commit
Mass-14's picture
Mass-14
Mirror of thenlper/gte-large
b4f5404 verified 11 months ago
  • openvino_model.bin
    1.34 GB
    xet
    Mirror of thenlper/gte-large 11 months ago
  • openvino_model.xml
    708 kB
    Mirror of thenlper/gte-large 11 months ago
  • openvino_model_qint8_quantized.bin
    337 MB
    xet
    Mirror of thenlper/gte-large 11 months ago
  • openvino_model_qint8_quantized.xml
    1.31 MB
    Mirror of thenlper/gte-large 11 months ago