Instructions to use team-lucid/layoutlmv3-base-ko with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use team-lucid/layoutlmv3-base-ko with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="team-lucid/layoutlmv3-base-ko")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("team-lucid/layoutlmv3-base-ko") model = AutoModel.from_pretrained("team-lucid/layoutlmv3-base-ko") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6ec5d5ced1099cb1c6ca58956b466b4013285096ea6669c7accd228b053a1dc2
- Size of remote file:
- 510 MB
- SHA256:
- 99c74e24b38a1525786cea8c6f47ba38944363b717701bca158300610fd4288a
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