README.md

---
title: T5 Email Summarizer Demo v3
emoji: 📧
colorFrom: blue
colorTo: green
sdk: gradio
sdk_version: 4.44.1
app_file: app.py
pinned: true
license: apache-2.0
models:
  - wordcab/t5-small-email-summarizer
datasets:
  - argilla/FinePersonas-Conversations-Email-Summaries
space_hardware: "cpu-basic"
---

# T5 Email Summarizer - Interactive Demo v3

This Space provides an interactive demo of the [wordcab/t5-small-email-summarizer](https://huggingface.co/wordcab/t5-small-email-summarizer) model.

## 🔧 v3 Major Updates

- **Separate Subject/Body fields** for better email structure
- **General title normalization** (Mr. → Mr, Dr. → Dr, Prof. → Prof)
- **Improved unicode handling** for special characters
- **Robust preprocessing** that handles all edge cases

## Features

- 🎯 **Dual-mode summarization**: Brief (1-2 sentences) or Full (detailed)
- 🚀 **Fast inference**: Quick processing even on CPU
- 💪 **Robust**: Handles typos, abbreviations, and informal language
- 🔄 **Auto-detect**: Automatically chooses brief or full based on email length
- 🔧 **Smart preprocessing**: General solution for title and unicode issues

## Model Details

- **Architecture**: T5-small (60M parameters)
- **Training Data**: [argilla/FinePersonas-Conversations-Email-Summaries](https://huggingface.co/datasets/argilla/FinePersonas-Conversations-Email-Summaries) (364K examples)
- **Max Input**: 512 tokens (~2500 characters)
- **License**: Apache 2.0

## Try It Out

1. Enter subject line (optional) and email body separately
2. Select summary type or use auto-detect
3. Click "Generate Summary"

The model will produce a concise, accurate summary with automatic normalization of titles and special characters!