Unconditional Image Generation
Transformers
PyTorch
English
pulse2pulse-2
ECG
Synthetic ECG
custom_code
Instructions to use deepsynthbody/deepfake_ecg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepsynthbody/deepfake_ecg with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("deepsynthbody/deepfake_ecg", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- c13ec37ca565dd589406cea1e73de0dc9343e56bea08759d9132132790f3ee95
- Size of remote file:
- 1.59 MB
- SHA256:
- 03ce3559e0770895d34b43157e2b7d6fbcf146552742df99fb6bc2152d84dc2f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.