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mrp
/
SCT_BERT_Mini

Sentence Similarity
sentence-transformers
PyTorch
Transformers
English
feature-extraction
Model card Files Files and versions
xet
Community
1

Instructions to use mrp/SCT_BERT_Mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use mrp/SCT_BERT_Mini with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("mrp/SCT_BERT_Mini")
    
    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 mrp/SCT_BERT_Mini with Transformers:

    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("mrp/SCT_BERT_Mini", dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
SCT_BERT_Mini
45.7 MB
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  • 1 contributor
History: 5 commits
mrp's picture
mrp
Update README.md
3eff4c9 over 2 years ago
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  • .gitattributes
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  • README.md
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  • config.json
    677 Bytes
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  • config_sentence_transformers.json
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  • modules.json
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  • pytorch_model.bin

    Detected Pickle imports (4)

    • "collections.OrderedDict",
    • "torch.FloatStorage",
    • "torch._utils._rebuild_tensor_v2",
    • "torch.LongStorage"

    What is a pickle import?

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  • sentence_bert_config.json
    53 Bytes
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  • special_tokens_map.json
    112 Bytes
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  • tokenizer.json
    712 kB
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  • tokenizer_config.json
    450 Bytes
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  • vocab.txt
    232 kB
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