---
license: apache-2.0
tags:
- vit
- ecg
- self-supervised
- contrastive-learning
---

# ViT-MAE ECG Encoder

This repository contains a Vision Transformer (ViT-MAE) model pretrained on ECG signals using masked autoencoding. It is a forked and modified version of the Hugging Face `transformers` library.

## Model Files

- `model.safetensors`: Model weights (~77MB) saved in `safetensors` format.
- `config.json`: Model architecture and configuration.

## Usage

To use this model, make sure to install the forked version of `transformers` (see below), which includes modifications for original implementations of ViTMAE model from HuggingFace.

```bash
git clone git@github.com:Alsalivan/ecgcmr.git
cd ecgcmr/external/transformers
pip install -e .
```

## Load model

```
from transformers import ViTMAEModel
model = ViTMAEModel.from_pretrained("alsalivan/vitmae_ecg")
```