Instructions to use Log95/layoutlm-funsd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Log95/layoutlm-funsd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Log95/layoutlm-funsd")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Log95/layoutlm-funsd") model = AutoModelForTokenClassification.from_pretrained("Log95/layoutlm-funsd", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6229cb4e37c1506e79be260b7b61e0e760f94e9bae11d25dc6071d2bd47f5790
- Size of remote file:
- 451 MB
- SHA256:
- 01d271cd9edb46544f6919f67c55ba22733c55e3d17a6c3a7f297de98ffba7a9
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