How to use JerryO3/test with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("JerryO3/test", trust_remote_code=True) sentences = [ "We therefore conducted a hospital based cross sectional study involving 101 HCWs from two facilities in Kumasi, Ghana to assess the level of preparedness of HCWs to respond to any possible EVD. METHODS: We administered a face-to-face questionnaire using an adapted WHO (2015) and CDC (2014) Checklist for Ebola Preparedness and assessed overall knowledge gaps, and preparedness of the Ghanaian HCWs in selected health facilities of the Ashanti Region of Ghana from October to December 2015. RESULTS: A total 92 (91.09%) HCWs indicated they were not adequately trained to handle an EVD suspected case. Only 25.74% (n = 26) considered their facilities sufficiently equipped to handle and manage EVD patients. When asked which disinfectant to use after attending to and caring for a suspected patient with EVD, only 8.91% (n = 9) could correctly identify the right disinfectant (χ(2) = 28.52, p = 0.001). CONCLUSION: Our study demonstrates poor knowledge and ill preparedness and unwillingness of many HCWs to attend to EVD. Beyond knowledge acquisition, there is the need for more training from time to time to fully prepare HCWs to handle any possible EVD case. Text: During the last outbreak of Ebola Virus Disease (EVD) and its consequential massive epidemic with very high mortality [1] , many health systems and services in West Africa were overwhelmed and disrupted.", "How many facilities believed they were adequately equipped to handle Ebla virus disease?", "What developments have been made possible by the study of B-cell repertoire?", "Where does the NLRP3 inflammasome activate after a SARS-CoV infection?" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
