How to use Abeshith/research-embedding-finetuned with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Abeshith/research-embedding-finetuned") sentences = [ "4b94d2486cf7181f8458d2496310f9b2", "Surface Disinfection. The patient-care areas in a dental setting become contaminated with bacterial and viral pathogens during patient treatment. Incorporating standard precautions set forth by CDC and OSHA guidelines will reduce the risk of disease transmission. Contaminated environmental surfaces, including clinical contact and housekeeping surfaces, become a reservoir of infectious material with the potential to spread an infection to health-care personnel and patients. Transmission of pathogens can occur by direct or indirect contact of clinical contact surfaces and the hands of health-care personnel. Proper infection control protocol of these surfaces includes cleaning, disinfecting, and the use of barriers to prevent the spread of infectious pathogens. This chapter will provide an overview of the disinfection protocol of environmental surfaces in the dental setting. The topics include the various chemical formulations of hospital disinfectants and their proper use, as well as physical barriers that aim to reduce the degree of contamination in the dental treatment area thus decreasing the probability of cross-infection and disease transmission", "scientific", "how long does coronavirus remain stable on surfaces?", "gegboxgs", "16", "mteb/trec-covid", "biomedical_literature_retrieval" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [8, 8]
