Instructions to use vedanthire/DONUT-LY-PROJECT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vedanthire/DONUT-LY-PROJECT with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("vedanthire/DONUT-LY-PROJECT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from vedanthire/DONUT-LY-PROJECT: direct link, hf CLI and curl.
- Browser
- Download file 362 Bytes
-
https://huggingface.co/vedanthire/DONUT-LY-PROJECT/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://vedanthire/DONUT-LY-PROJECT/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/vedanthire/DONUT-LY-PROJECT/resolve/main/preprocessor_config.json
362 Bytes
| { | |
| "do_align_long_axis": false, | |
| "do_normalize": true, | |
| "do_pad": true, | |
| "do_resize": true, | |
| "do_thumbnail": true, | |
| "feature_extractor_type": "DonutFeatureExtractor", | |
| "image_mean": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "image_std": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "processor_class": "DonutProcessor", | |
| "resample": 2, | |
| "size": [ | |
| 960, | |
| 1280 | |
| ] | |
| } | |