Instructions to use elvinaqa/layoutlm-funsd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use elvinaqa/layoutlm-funsd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="elvinaqa/layoutlm-funsd")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("elvinaqa/layoutlm-funsd") model = AutoModelForTokenClassification.from_pretrained("elvinaqa/layoutlm-funsd", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 98f4bf5edf725605dd7111c075946867660856bd6ff4aac0d915f59e42f0871e
- Size of remote file:
- 3.38 kB
- SHA256:
- caad0fcff52df07f4c821bacc487d1d59de52a43e4d4b9880751d12996713233
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