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noace
/
bge-m3-banking-v2-final

Sentence Similarity
sentence-transformers
Safetensors
xlm-roberta
feature-extraction
dense
Generated from Trainer
dataset_size:3379
loss:CosineSimilarityLoss
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use noace/bge-m3-banking-v2-final with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use noace/bge-m3-banking-v2-final with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("noace/bge-m3-banking-v2-final")
    
    sentences = [
        "nếu ngày điều chỉnh lãi suất trùng ngày nghỉ, sẽ tính vào ngày làm việc liền kề trước đó.",
        "lãi suất tài khoản thanh toán vnd là 0,3%/năm cho số dư trên 100 triệu.",
        "tài khoản vé số không dùng để chứa tiền.",
        "trường hợp ngày 27/08 là ngày lễ, lãi suất sẽ được xác định vào ngày làm việc ngay trước đó."
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
bge-m3-banking-v2-final
2.29 GB
Ctrl+K
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  • 1 contributor
History: 2 commits
noace's picture
noace
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  • 1_Pooling
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  • .gitattributes
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  • README.md
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  • config.json
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  • config_sentence_transformers.json
    283 Bytes
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  • model.safetensors
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  • modules.json
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  • sentence_bert_config.json
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  • sentencepiece.bpe.model
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  • special_tokens_map.json
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  • tokenizer.json
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  • tokenizer_config.json
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