Instructions to use dodogigi/layoutlm-funsd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dodogigi/layoutlm-funsd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="dodogigi/layoutlm-funsd")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("dodogigi/layoutlm-funsd") model = AutoModelForTokenClassification.from_pretrained("dodogigi/layoutlm-funsd", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from dodogigi/layoutlm-funsd: direct link, hf CLI and curl.
- Browser
- Download file 225 Bytes
-
https://huggingface.co/dodogigi/layoutlm-funsd/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://dodogigi/layoutlm-funsd/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/dodogigi/layoutlm-funsd/resolve/main/preprocessor_config.json
225 Bytes
| { | |
| "apply_ocr": true, | |
| "do_resize": true, | |
| "feature_extractor_type": "LayoutLMv2FeatureExtractor", | |
| "ocr_lang": null, | |
| "processor_class": "LayoutLMv2Processor", | |
| "resample": 2, | |
| "size": 224, | |
| "tesseract_config": "" | |
| } | |