sentence-transformers How to use pj-mathematician/JobSkillBGE-large-en-v1.5 with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("pj-mathematician/JobSkillBGE-large-en-v1.5")
sentences = [
"For roles such as 'physiotherapist', 'neuromusculoskeletal physiotherapist', 'osteopath', and 'chiropractor', the skills needed include a deep understanding of human anatomy and physiology, strong diagnostic skills, and the ability to apply manual therapy techniques to treat musculoskeletal issues. Additionally, effective communication skills are crucial for explaining treatments and exercises to patients, while adaptability and problem-solving skills are essential for tailoring treatments to individual patient needs.",
"Job roles such as insulation installers, HVAC technicians, and construction engineers require knowledge of various types and characteristics of insulation materials to effectively reduce heat transfer and improve energy efficiency in buildings and systems. Understanding the typology of insulation materials, including their thermal properties, durability, and environmental impact, is crucial for these professionals to select the most appropriate materials for specific applications.",
"Job roles such as Contract Managers, Legal Analysts, and Compliance Officers require the skill of reviewing or auditing completed contracts to ensure legal accuracy, compliance with regulations, and alignment with organizational goals.",
"Job roles that require skills in dealing with emergency care situations include emergency medical technicians (EMTs), paramedics, and emergency room nurses or doctors, all of whom must quickly and effectively manage critical health situations to save lives."
]
embeddings = model.encode(sentences)
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4] 
