README.md

metadata

library_name: onnx
tags:
  - email-classification
  - job-search
  - onnx
  - transformers.js
  - browser-ml
license: mit
datasets:
  - custom
language:
  - en
pipeline_tag: text-classification

Email Classifier for Job Applications

A fine-tuned BGE-small model that classifies emails into job application categories. Designed to run entirely in the browser using ONNX Runtime Web.

Model Description

• Base Model: BAAI/bge-small-en-v1.5
• Task: 5-class email classification
• Format: ONNX (optimized for browser inference)
• Size: ~128MB

Labels

Label	Description	Application Status
confirmation	Application received/confirmed	Applied
rejection	Application rejected	Rejected
interview	Interview invitation	Interviewing
offer	Job offer	Offer
not_job	Not job-related	-

Performance

• Validation Accuracy: 99.65%
• Training Data: 28,500 synthetic + curated emails

Usage with ONNX Runtime Web

import * as ort from 'onnxruntime-web';

// Load model
const session = await ort.InferenceSession.create(
  'https://huggingface.co/YOUR_USERNAME/email-classifier/resolve/main/model.onnx'
);

// Tokenize and run inference
const results = await session.run({
  input_ids: inputIdsTensor,
  attention_mask: attentionMaskTensor,
});

Files

• model.onnx - The ONNX model file
• vocab.txt - Vocabulary file for tokenization
• config.json - Model configuration

Privacy

This model runs 100% client-side in the browser. No email data is ever sent to a server.

License

MIT