How to use from the
Use from the
sentence-transformers library
from sentence_transformers import SentenceTransformer

model = SentenceTransformer("swaraj20/resume_gte_embedding")

sentences = [
    "PERSONAL SKILLS • Quick learner, • Eagerness to learn new things, • Competitive attitude, • Good leadership qualities, • Ability to deal with people diplomatically. PERSONAL DOSSIER Fathers Name: Dhanraj WaghEducation Details \r\nJanuary 2012 to January 2016 Bachelors of Engineering Engineering Pune, Maharashtra Pune University\r\nJanuary 2012 Higher Secondary Certificate  Nashik, Maharashtra SND College of Engineering and Research Center\r\nJanuary 2010 Secondary School Certificate  Yeola, Maharashtra Swami Muktanand Jr. College\r\n HSC   Maharashtra State Board\r\n SSC   Maharashtra State Bard\r\n BE  Rajapur, Uttar Pradesh Madhyamik Vidya Mandir Rajapur\r\nTesting and Quality Control Engineer \r\n\r\nTesting and Quality Control Engineer - M/S Rakesh Transformer Industries Pvt. Ltd\r\nSkill Details \r\nCompany Details \r\ncompany - M/S Rakesh Transformer Industries Pvt. Ltd\r\ndescription - Responsibilities:\r\n•     To conduct Routine test, Type Test (Temperature Rise Test), Special Test on Transformers as per IS & IEC up\r\n\r\nto - 10 MVA / 33 KV Class & preparing of its test reports.\r\n\r\n•     Routine tests, Type tests and Special tests as per IS 2026, IS 1180, IS 11171/IEC-60076- test\r\n\r\nManual/inspection plans of Power Transformers, Distribution Transformers, Inverter Duty, Converter Duty,\r\n\r\nMotor Duty Transformer, Furnace Transformer, Auto Transformers, Dry Type (VPI & CRT) LT Transformers,\r\n\r\nSpecial Transformers\r\n•     Testing Remote Tap Changer Cubicle (RTCC) Panel with OLTC and its operation ( CTR, Esun MR.)\r\n\r\n•     Functional Testing of Transformer Accessories ( BR, PRV, MOG, WTI, OTI and its Setting)\r\n\r\n•     In case any failure in testing analyses the root cause and submit the CAPA\r\n\r\n•     Assist the customer or their representative at the time of inspection.\r\n\r\n•     In process testing of winding, core assembly and core coil assembly.\r\n\r\n•     Handling 3rd party and Government Body's Inspection.\r\n\r\n•     Preparation of Daily Internal Testing Reports and send to concern.\r\n\r\n•     Support Certification Audits (ISO & BIS)\r\n\r\n•     Calibration/validation of tools, instruments, Measuring equipment's\r\n\r\n•     Suggest the client about proper maintenance of transformer\r\n•     Doing all documentation and Maintain Records and Analyze the Test Results and Maintain Testing Ledger\r\n\r\n•     In process Quality Inspection of Winding, Core assembly, Core Coil assembly as per Standard and as per\r\n\r\norganizational Norms.\r\n\r\n•     Pre Dispatch Quality Inspection of Complete Product.\r\n\r\n•     Implementation of, WHY-WHY analysis.\r\ncompany - M/S Silverline Electricals Pvt. Ltd\r\ndescription - Routine tests, Type tests (Temperature Rise Test) and Special tests as per IS 2026, IS 1180/ test\r\n\r\nManual/inspection plans of Distribution Transformer, Power Transformer\r\n\r\n•     Successfully handled Responsibilities of ERDA's testing.\r\n\r\n•     On site commissioning of Transformer.\r\n\r\n•     Assist the customer or their representative at the time of inspection.\r\n\r\n•     In process testing of winding, core assembly and core coil assembly.\r\n\r\n•     Successfully handling 3rd party and Government Body's Inspection\r\n\r\n•     Preparation of Daily Internal Testing Reports and send to concern.\r\n\r\n•     Suggest the client about proper maintenance of transformer",
    "• Good logical and analytical skills • Positive attitude towards solving problems and accepting challenges • A team player & leader • A good organizer PRESONAL DETAILS: DOB: 20/07/1995. Marital status: Single.Education Details July 2015 to June 2018 BE Electrical Pune, Maharashtra Sinhagad institute of technology January 2012 DIPLOMA MSBTE Kopargaon, MAHARASHTRA, IN K.B.P.Polytechnic January 2010 SSC S.G.Vidyalaya state board Testing Engineer Electrical engineer Skill Details Company Details company - Intelux Electronics Pvt Ltd description - 1. Power management system Testing department",
    "We are looking for a skilled Java Developer to join our team. The ideal candidate should have expertise in industry-standard tools and techniques relevant to Java Developer roles.",
    "We are looking for a skilled Testing to join our team. The ideal candidate should have expertise in industry-standard tools and techniques relevant to Testing roles."
]
embeddings = model.encode(sentences)

similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4]

📂 Dataset

This model was fine-tuned on the Resume Dataset from Kaggle(https://www.kaggle.com/datasets/palaksood97/resume-dataset/discussion/174335), containing resumes categorized by job roles. The data was used to generate similarity pairs and synthetic job descriptions for training.

🧠 Resume GTE Embedding Model

A domain-specific sentence embedding model fine-tuned on resumes using GTE-base. Built for use in HR systems, resume search engines, talent matching, and AI-driven hiring.


📌 Model Card

  • Base Model: thenlper/gte-base
  • Fine-tuned on:
    • Self-supervised resume chunks
    • Resume pairs with similar job roles (category-based)
    • Resume ↔ synthetic job description pairs
  • Dataset Size: 4,169+ semantic chunks
  • Loss: CosineSimilarityLoss
  • Vector Output Size: 768
  • Chunking: Semantic section-based splitting (e.g., “Work Experience”, “Skills”, etc.)

🧪 Intended Use Cases

  • ✅ Resume similarity search
  • ✅ Resume ↔ Job description matching
  • ✅ Candidate clustering by skills or experience
  • ✅ Career path embeddings / recommendation

🚀 Example Usage (Python)

from sentence_transformers import SentenceTransformer, util

model = SentenceTransformer("swaraj20/resume_gte_embedding")

resume1 = "Experienced software engineer skilled in Python, ML, and cloud deployment."
resume2 = "Looking for a backend developer with Python and AWS experience."

embedding1 = model.encode(resume1, convert_to_tensor=True)
embedding2 = model.encode(resume2, convert_to_tensor=True)

similarity = util.cos_sim(embedding1, embedding2)
print(f"Similarity Score: {similarity.item():.4f}")
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