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noace
/
mpnet-final

Sentence Similarity
sentence-transformers
Safetensors
xlm-roberta
feature-extraction
dense
Generated from Trainer
dataset_size:1109
loss:MatryoshkaLoss
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use noace/mpnet-final with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use noace/mpnet-final with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("noace/mpnet-final")
    
    sentences = [
        "Lãi suất vay tiêu dùng từ thẻ kỳ hạn 2-5 tháng là 12%/năm.",
        "Mức lãi suất áp dụng cho khoản vay tiêu dùng thẻ kỳ hạn ngắn (2-5 tháng) là 12%.",
        "Hạn dùng ưu đãi của khách hàng VIP được tính theo năm dương lịch hưởng quyền lợi.",
        "dịch vụ áp dụng cho nhân viên sacombank được ủy quyền sử dụng thẻ"
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
mpnet-final
1.13 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
noace's picture
noace
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3a70bc9 verified 4 months ago
  • 1_Pooling
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  • .gitattributes
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  • README.md
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  • config.json
    691 Bytes
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  • config_sentence_transformers.json
    358 Bytes
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  • model.safetensors
    1.11 GB
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  • modules.json
    229 Bytes
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  • sentence_bert_config.json
    57 Bytes
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  • sentencepiece.bpe.model
    5.07 MB
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  • special_tokens_map.json
    964 Bytes
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  • tokenizer.json
    17.1 MB
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  • tokenizer_config.json
    1.37 kB
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