Instructions to use team-lucid/layoutlmv3-small-ko with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use team-lucid/layoutlmv3-small-ko with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="team-lucid/layoutlmv3-small-ko")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("team-lucid/layoutlmv3-small-ko") model = AutoModel.from_pretrained("team-lucid/layoutlmv3-small-ko") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 14b24e39a1878b015acd10aa2c2e3c84fabfa752f935809dd4643ca89c9f59dd
- Size of remote file:
- 169 MB
- SHA256:
- 3ff3d33b154e4063e839dbc07d383c3503739472c91c9a5c2d0dadbecfe10130
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