---
title: MMRM
emoji: 🐠
colorFrom: yellow
colorTo: blue
sdk: gradio
sdk_version: 6.5.1
app_file: app.py
pinned: false
license: gpl-3.0
short_description: 'Restoring Ancient Ideograph: A Multimodal Multitask Neural N'
---


Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

## Interactive Demo

This Gradio app demonstrates the restoration capabilities of the MMRM model compared to textual and visual baselines on real-world damaged character data.

### Features
- **Real-world Data**: Select from samples in the `data/real` directory.
- **Model Comparison**:
  - **Zero-shot Baseline**: Pre-trained GuwenBERT (Works out-of-the-box without training).
  - **Textual Baseline**: Fine-tuned RoBERTa.
  - **Visual Baseline**: ResNet50.
  - **MMRM**: Our proposed Multimodal Multitask Restoring Model.
- **Intermediate Visualization**: Shows the restored image generated by the MMRM capability.

### Running the Demo

1. **Deploy to Hugging Face Spaces**:
   - Create a new Space on Hugging Face (SDK: Gradio).
   - Upload the contents of this `demo` folder to the Space repository.
   - Upload your model checkpoints to the `checkpoints/` folder in the Space.
     - `checkpoints/phase2_mmrm_best.pt`
     - `checkpoints/phase1_roberta_finetuned.pt`
     - `checkpoints/baseline_img.pt`
   
   *Note: Even without checkpoints, the demo will run using the Zero-shot Baseline (downloaded automatically).*
   
2. **Local Testing**:
   - Install requirements: `pip install -r requirements.txt`
   - Run: `python app.py` (assuming you are inside the `demo` directory)