---
license: mit
---

# Model Card for DiffuSETS

## Description

<!-- Provide a longer summary of what this model is. -->

- **Developed by:** Yongfan Lai
- **License:** mit


### Source Code

<!-- Provide the basic links for the model. -->

- **Repository:** [Github](https://github.com/Raiiyf/text2ecg)

### Assets List

- **prerequisites_for_inference.zip**:
```
prerequisites/
├── clf_data/ : Directory contains data for imbalanced classification experiments 
├── clip_model.pth : CLIP model checkpoints.
├── mimic_vae_lite_0_new.pt : Subsets of VAE encoding latents of MIMIC IV ECG dataset.
├── ptbxl_text_embed.csv : Pre-generated text embeddings of PTB-XL dataset
├── ptbxl_vae.pt : VAE encoding latents of PTB-XL dataset.
├── unet_all.pth : A pretrained full capacity DiffuSETS model.
└── vae_model.pth : VAE model checkpoints suit for the unet model and latent datasets above.
```

- **mimic_vae_lite_0_new.zip**:
```
prerequisites/
└── mimic_vae_0_new.pt: VAE encoding latents of MIMIC IV ECG dataset. Only needed while training.
```

## Usage


**Quick Start:** Download and unzip the prerequisites_for_inference.zip, place the `./prerequisites` folder under repo's root, then start ECG generation through

```sh
python DiffuSETS_inference.py path/to/your/config.json
```

or

```sh
python -m test_scripts.diversity
```

**For users want to train from scratch:** Besides above prerequisites_for_inference.zip, the mimic_vae_0_new.pt (training data encoded by vae) should also be downloaded and put into the `./prerequisites` folder.

For more details about training and inference, please refer to our [github repo page](https://github.com/Raiiyf/text2ecg)