| # 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** 🛠️ |