How to use yasserrmd/pediatrics-gemma-300m-emb with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("yasserrmd/pediatrics-gemma-300m-emb") sentences = [ "What are the main clinical manifestations and characteristics of congenital syphilis?", "Trained staff in community health centers obtain information on infant weight during periodic visits scheduled at three and six months. Age- and sex-adjusted standard deviation scores (SDS) for weight are calculated using Dutch reference curves. Infant growth rates of weight gain in the first three and six months after birth are then calculated by comparing the weight at three or six months to the birth weight SDS. These growth rates provide information on the infant's growth trajectory and can help identify any deviations from the norm.", "The main clinical manifestations of congenital syphilis include prematurity, low birth weight, hepatomegaly with or without splenomegaly, cutaneous lesions, limb pseudoparalysis, respiratory distress, jaundice, anemia, generalized lymphadenopathy, and osteitis and osteochondritis. Late congenital syphilis is characterized by saber shin deformity of the tibia, Clutton's joints, frontal bossing, saddle nose, deformed upper medial incisor teeth (Hutchinson's teeth), neurological deafness, and difficulty in learning.", "When evaluating newborns, orthopaedic surgeons should consider risk factors such as difficult vaginal delivery of a large infant, which can be associated with fractures or brachial plexus injury, and breech position, which can be associated with developmental dysplasia of the hip (DDH). They should also be aware of conditions like Klippel-Feil syndrome, congenital muscular torticollis, arthrogryposis, and neurologic problems indicated by a high arch in the feet." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
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