{} | |
# DONUT Cord-v2 | |
<a href="https://x.com/nearcyan/status/1706914605262684394"> | |
<div style="text-align: center;"> | |
<picture> | |
<source media="(prefers-color-scheme: dark)" srcset="https://huggingface.co/de-Rodrigo/donut-cord-v2/resolve/main/assets/dragon_huggingface.png"> | |
<source media="(prefers-color-scheme: light)" srcset="https://huggingface.co/de-Rodrigo/donut-cord-v2/resolve/main/assets/dragon_huggingface.png"> | |
<img alt="DragonHuggingFace" src="https://huggingface.co/de-Rodrigo/donut-cord-v2/resolve/main/assets/dragon_huggingface.png" style="width: 200px;"> | |
</picture> | |
</div> | |
</a> | |
## Model Architecture | |
**This model is based on the Donut architecture and fine-tuned on the Cord-v2 dataset for form understanding tasks.** | |
- Backbone: [Donut](https://huggingface.co/naver-clova-ix/donut-base) | |
- Training Data: [Cord-v2](https://huggingface.co/datasets/naver-clova-ix/cord-v2) | |
## Example Usage | |
```python | |
from transformers import AutoProcessor, AutoModel | |
processor = AutoProcessor.from_pretrained("de-Rodrigo/donut-merit") | |
model = AutoModel.from_pretrained("de-Rodrigo/donut-merit") | |
``` | |
**WIP** 🛠️ |