Instructions to use katanaml/donut-demo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use katanaml/donut-demo with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "image-to-text" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("image-to-text", model="katanaml/donut-demo")# Load model directly from transformers import AutoTokenizer, AutoModelForImageTextToText tokenizer = AutoTokenizer.from_pretrained("katanaml/donut-demo") model = AutoModelForImageTextToText.from_pretrained("katanaml/donut-demo") - Notebooks
- Google Colab
- Kaggle
| license: mit | |
| datasets: | |
| - naver-clova-ix/cord-v2 | |
| metrics: | |
| - accuracy | |
| pipeline_tag: image-to-text | |
| Donut model finetuned with CORD dataset. Mean accuracy: 0.901198895445646 | |
| - [Katana ML](https://katanaml.io) | |
| - [Sparrow GitHub](https://github.com/katanaml/sparrow) |