Sentence Similarity
sentence-transformers
Safetensors
feature-extraction
dense
Generated from Trainer
dataset_size:800
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
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
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