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Moonreif
/
bge-m3-quantized

Sentence Similarity
sentence-transformers
Safetensors
xlm-roberta
feature-extraction
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use Moonreif/bge-m3-quantized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use Moonreif/bge-m3-quantized with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("Moonreif/bge-m3-quantized")
    
    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
bge-m3-quantized
3.65 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
Moonreif's picture
Moonreif
Upload bge_m3_quantized.pt with huggingface_hub
7e53304 verified 16 days ago
  • 1_Pooling
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  • .gitattributes
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  • README.md
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  • bge_m3_quantized.pt

    Detected Pickle imports (9)

    • "torch.FloatStorage",
    • "torch._utils._rebuild_parameter",
    • "torch.LongStorage",
    • "torch.qint8",
    • "torch.per_tensor_affine",
    • "torch._utils._rebuild_tensor_v2",
    • "torch._utils._rebuild_qtensor",
    • "collections.OrderedDict",
    • "torch.QInt8Storage"

    How to fix it?

    1.36 GB
    xet
    Upload bge_m3_quantized.pt with huggingface_hub 16 days ago
  • config.json
    744 Bytes
    Add new model. 16 days ago
  • config_sentence_transformers.json
    284 Bytes
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  • model.safetensors
    2.27 GB
    xet
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  • modules.json
    429 Bytes
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  • sentence_bert_config.json
    241 Bytes
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  • tokenizer.json
    17.1 MB
    xet
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  • tokenizer_config.json
    409 Bytes
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