How to use vaktibabat/heart-e5 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("vaktibabat/heart-e5") sentences = [ "query: which structure forms the floor and part of the walls of the third ventricle", "passage: Calories Lost in an Hour Long Yoga Class High Calorie Burn. If you've decided to take up yoga with the intention of burning calories quickly to develop a fit body, Bikram and Vinyasa yoga are your top choices, according to HealthStatus. The website reports a 145-pound person will burn 461 calories in an hour-long Bikram yoga class; this form of yoga also goes by the name hot yoga. The same person will burn 574 calories in 60 minutes of Vinyasa yoga.", "passage: Ventricles of the Brain The rest of the CSF production is the result of transependymal flow from the brain to the ventricles. CSF flows from the lateral ventricles, through the interventricular foramens, and into the third ventricle, cerebral aqueduct, and the fourth ventricle.ateral ventricles. The largest cavities of the ventricular system are the lateral ventricles. Each lateral ventricle is divided into a central portion, formed by the body and atrium (or trigone), and 3 lateral extensions or horns of the ventricles.", "passage: Third Ventricle The floor of the third ventricle is formed by a number of structures including the hypothalamus, subthalamus, mammilary bodies, infundibulum (pituitary stalk), and the tectum of the midbrain. The lateral walls of the third ventricle are formed by the walls of the left and right thalamus." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
