Model Card for DiffuSETS
Description
- Developed by: Yongfan Lai
- License: mit
Source Code
- Repository: Github
Assets List
- prerequisites_for_inference.zip:
prerequisites/
βββ clf_data/ : Directory contains data for imbalanced classification experiments
βββ clip_model.pth : CLIP model checkpoints.
βββ mimic_vae_lite_0_new.pt : Subsets of VAE encoding latents of MIMIC IV ECG dataset.
βββ ptbxl_text_embed.csv : Pre-generated text embeddings of PTB-XL dataset
βββ ptbxl_vae.pt : VAE encoding latents of PTB-XL dataset.
βββ unet_all.pth : A pretrained full capacity DiffuSETS model.
βββ vae_model.pth : VAE model checkpoints suit for the unet model and latent datasets above.
- mimic_vae_lite_0_new.zip:
prerequisites/
βββ 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
python DiffuSETS_inference.py path/to/your/config.json
or
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
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