File size: 1,133 Bytes
7af424f adda8d8 5db87a1 adda8d8 5db87a1 adda8d8 5db87a1 adda8d8 5db87a1 adda8d8 5db87a1 adda8d8 5db87a1 adda8d8 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 |
---
{}
---
# DONUT Merit
<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-merit/resolve/main/assets/dragon_huggingface.png">
<source media="(prefers-color-scheme: light)" srcset="https://huggingface.co/de-Rodrigo/donut-merit/resolve/main/assets/dragon_huggingface.png">
<img alt="DragonHuggingFace" src="https://huggingface.co/de-Rodrigo/donut-merit/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 Merit dataset for form understanding tasks.**
- Backbone: [Donut](https://huggingface.co/naver-clova-ix/donut-base)
- Training Data: [Merit](https://huggingface.co/datasets/de-Rodrigo/merit)
## 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** 🛠️ |