Instructions to use thaind/layoutlmv2-jaen-gemai with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thaind/layoutlmv2-jaen-gemai with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="thaind/layoutlmv2-jaen-gemai")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("thaind/layoutlmv2-jaen-gemai") model = AutoModelForTokenClassification.from_pretrained("thaind/layoutlmv2-jaen-gemai") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3b490c2b7112cc571ae8aeb6547392195595a528372c253bfe353762c0e4053b
- Size of remote file:
- 2.35 kB
- SHA256:
- 00314c15c084414b7d409c42c18a24596eaff5814c716047087f32076756a7b7
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