Instructions to use muhammadummerrr/donut-receipt-lora-testing-adapter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use muhammadummerrr/donut-receipt-lora-testing-adapter with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Bennet1996/donut-small") model = PeftModel.from_pretrained(base_model, "muhammadummerrr/donut-receipt-lora-testing-adapter") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from muhammadummerrr/donut-receipt-lora-testing-adapter: direct link, hf CLI and curl.
- Browser
- Download file 439 Bytes
-
https://huggingface.co/muhammadummerrr/donut-receipt-lora-testing-adapter/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://muhammadummerrr/donut-receipt-lora-testing-adapter/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/muhammadummerrr/donut-receipt-lora-testing-adapter/resolve/main/preprocessor_config.json
439 Bytes
| { | |
| "do_align_long_axis": false, | |
| "do_normalize": true, | |
| "do_pad": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "do_thumbnail": true, | |
| "image_mean": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "image_processor_type": "DonutImageProcessor", | |
| "image_std": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "processor_class": "DonutProcessor", | |
| "resample": 2, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "height": 960, | |
| "width": 720 | |
| } | |
| } | |