Instructions to use Ssunbell/layoutlmv2_large_sequence with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ssunbell/layoutlmv2_large_sequence with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Ssunbell/layoutlmv2_large_sequence")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("Ssunbell/layoutlmv2_large_sequence") model = AutoModel.from_pretrained("Ssunbell/layoutlmv2_large_sequence") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6a40a8294d8a76560b043a88dae288074c8902335deef7a9b9b87c6e419c1f2d
- Size of remote file:
- 1.71 GB
- SHA256:
- 5afb23aa160676c44123c670c644ff1c3f641e6970425498c0bc4e3cba94ea44
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