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ChenyuEcho
/
hospital_qapairs_modinmod_oldtrainmethod

Sentence Similarity
sentence-transformers
Safetensors
feature-extraction
dense
Generated from Trainer
dataset_size:800
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
Model card Files Files and versions
xet
Community

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

  • Libraries
  • sentence-transformers

    How to use ChenyuEcho/hospital_qapairs_modinmod_oldtrainmethod with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("ChenyuEcho/hospital_qapairs_modinmod_oldtrainmethod")
    
    sentences = [
        "Qual é o problema reportado por Brian K. Lee ao suporte de TI?",
        "Delays in initiating palliative care consults in the acute care unit and a request to review and streamline the referral triggers/protocol.",
        "Teclas aderentes no teclado dificultam a digitação dos dados dos pacientes críticos nos sistemas de ventilação e monitoramento, com urgência para evitar atrasos nos protocolos de oxigenoterapia.",
        "Cefepime injectable is in short supply. The thread proposes revising the administration plan, considering alternative antibiotics, informing frontline nurses, and coordinating with Pharmacy Services."
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
hospital_qapairs_modinmod_oldtrainmethod
31.7 MB
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  • 1 contributor
History: 2 commits
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ChenyuEcho
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  • config_sentence_transformers.json
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  • modules.json
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  • sentence_bert_config.json
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  • tokenizer.json
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  • tokenizer_config.json
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