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---
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
```javascript
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
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