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| 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! |