How to use StephKeddy/sbert-IR-covid-search with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("StephKeddy/sbert-IR-covid-search") sentences = [ "how has lack of testing availability led to underreporting of true incidence of Covid-19?", "can an effective sars-cov-2 vaccine be developed for the older population [SEP] the emergence of sars-cov-2 and its inordinately rapid spread is posing severe challenges to the wellbeing of millions of people worldwide, health care systems and the global economy. we aim to provide a platform exclusively for discussions of individual and age differences in susceptibility and immune responses to covid caused by sars-cov-2 infection and how to prevent or reduce severity of disease in older adults.", "the impact of changes in diagnostic testing practices on estimates of covid-19 transmission in the united states [SEP] estimates of the reproductive number for novel pathogens such as sars-cov-2 are essential for understanding the potential trajectory of the epidemic and the level of intervention that is needed to bring the epidemic under control. however, most methods for estimating the basic reproductive number (r(0)) and time-varying effective reproductive number (r(t)) assume that the fraction of cases detected and reported is constant through time.", "nan" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
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