How to use shankerram3/resumator with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("shankerram3/resumator") sentences = [ "Name: Jane Doe\nTitles: Software Developer, Software Engineer\nSkills: Python, React, PostgreSQL, TypeScript\nExperience: 4 years\nResume: Full-stack engineer with 4 years building web applications using Python and React. Experience with PostgreSQL, REST APIs, and cloud deployment.", "Title: Senior Software Engineer\nCompany: TechCorp\nDescription: Looking for full-stack engineer with Python and React experience. Must have 3+ years building web applications.", "Title: Data Scientist\nCompany: DataCo\nDescription: Seeking data scientist with deep learning experience. PhD preferred. Must have publications in top ML conferences.", "Title: Truck Driver\nCompany: FreightCo\nDescription: CDL required, long-haul routes across the Midwest. Clean driving record mandatory." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
