Token Classification
Transformers
Safetensors
English
layoutlmv3
document-ai
document-understanding
key-information-extraction
conformal-prediction
uncertainty-quantification
calibration
wacv-2027
calidoc
Instructions to use MHamdan/calidoc-layoutlmv3-large-funsd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MHamdan/calidoc-layoutlmv3-large-funsd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="MHamdan/calidoc-layoutlmv3-large-funsd")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("MHamdan/calidoc-layoutlmv3-large-funsd") model = AutoModelForTokenClassification.from_pretrained("MHamdan/calidoc-layoutlmv3-large-funsd", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download processor_config.json from MHamdan/calidoc-layoutlmv3-large-funsd: direct link, hf CLI and curl.
- Browser
- Download file 495 Bytes
-
https://huggingface.co/MHamdan/calidoc-layoutlmv3-large-funsd/resolve/main/processor_config.json
- Command line
-
hf download hf://MHamdan/calidoc-layoutlmv3-large-funsd/processor_config.json
-
curl -L -o processor_config.json https://huggingface.co/MHamdan/calidoc-layoutlmv3-large-funsd/resolve/main/processor_config.json
495 Bytes
| { | |
| "image_processor": { | |
| "apply_ocr": false, | |
| "do_normalize": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_mean": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "image_processor_type": "LayoutLMv3ImageProcessor", | |
| "image_std": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "resample": 2, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "height": 224, | |
| "width": 224 | |
| }, | |
| "tesseract_config": "" | |
| }, | |
| "processor_class": "LayoutLMv3Processor" | |
| } | |