Instructions to use pvbhanuteja/layoutlm-funsd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pvbhanuteja/layoutlm-funsd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="pvbhanuteja/layoutlm-funsd")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("pvbhanuteja/layoutlm-funsd") model = AutoModelForTokenClassification.from_pretrained("pvbhanuteja/layoutlm-funsd", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 225 Bytes
8821621 | 1 2 3 4 5 6 7 8 9 10 11 | {
"apply_ocr": true,
"do_resize": true,
"feature_extractor_type": "LayoutLMv2FeatureExtractor",
"ocr_lang": null,
"processor_class": "LayoutLMv2Processor",
"resample": 2,
"size": 224,
"tesseract_config": ""
}
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