Object Detection
Transformers
PyTorch
TensorBoard
layoutlm
token-classification
Generated from Trainer
endpoints-template
Instructions to use Narsil/layoutlm-funsd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Narsil/layoutlm-funsd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="Narsil/layoutlm-funsd")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Narsil/layoutlm-funsd") model = AutoModelForTokenClassification.from_pretrained("Narsil/layoutlm-funsd") - Notebooks
- Google Colab
- Kaggle
Upload preprocessor_config.json with huggingface_hub
Browse files- preprocessor_config.json +9 -0
preprocessor_config.json
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{
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"apply_ocr": true,
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"do_resize": true,
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"feature_extractor_type": "LayoutLMv2FeatureExtractor",
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"ocr_lang": null,
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"processor_class": "LayoutLMv2Processor",
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"resample": 2,
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"size": 224
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}
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