Token Classification
Transformers
PyTorch
English
layoutlmv3
Generated from Trainer
token_classifier
layout_analysis
Eval Results (legacy)
Instructions to use Mit1208/layoutlmv3-finetuned-DocLayNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mit1208/layoutlmv3-finetuned-DocLayNet with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Mit1208/layoutlmv3-finetuned-DocLayNet")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("Mit1208/layoutlmv3-finetuned-DocLayNet") model = AutoModelForTokenClassification.from_pretrained("Mit1208/layoutlmv3-finetuned-DocLayNet") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1133e07e56bef4818e52c885428d878a365af13aaf492891eae5d973b1726902
- Size of remote file:
- 3.52 kB
- SHA256:
- f93ec3cb78e51aa96417ff32694ed72c8ff994d2a077d564271e1e3d48addd3d
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