Instructions to use AndreasPiper/layoutlm-funsd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AndreasPiper/layoutlm-funsd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="AndreasPiper/layoutlm-funsd")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("AndreasPiper/layoutlm-funsd") model = AutoModelForTokenClassification.from_pretrained("AndreasPiper/layoutlm-funsd") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7b6fd0cc3fb092b2a0e9116fb0a2fe410e149f62d30338be60d001532d3cad5e
- Size of remote file:
- 451 MB
- SHA256:
- 0aadcdd5fb7f3abadf2bba739e4da5d5c212ec85ab9492c05761aaade862a60d
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