oussama120/Resume_Sentence_Classification

DistilBERT Resume Classification Model

This repository contains a fine-tuned DistilBERT model for classifying resume sentences into predefined categories. The model is trained on a dataset of resumes and can classify sentences into categories such as Personal Information, Experience, Summary, Education, Qualifications & Certificates, Skills, and Objectives.

Model Details

• Model: DistilBERT (base-uncased)
• Fine-tuned on: Custom resume dataset (ganchengguang/resume_seven_class)
• Number of classes: 7

Categories

The model can classify sentences into the following categories:

• Personal Information
• Experience
• Summary
• Education
• Qualifications & Certificates
• Skills
• Objectives

Usage

Load the Model and Tokenizer

To use the model and tokenizer, you can load them from the Hugging Face Hub as follows:

from transformers import DistilBertTokenizerFast, DistilBertForSequenceClassification

# Load the model and tokenizer
model_name = "oussama120/Resume_Sentence_Classification"
tokenizer = DistilBertTokenizerFast.from_pretrained(model_name)
model = DistilBertForSequenceClassification.from_pretrained(model_name)