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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8638286ec70cf59764bd7b5e1da74cbe85cf9c6d347d9db52b0568b557a1946e
- Size of remote file:
- 4.09 kB
- SHA256:
- 8b08275d04e65e48e6b3cbb0b2a38b8533e009119fae3888a5b5877bd6356e96
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