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:
- b3726e0a443952d77bbf777b5ff367583d9044969436f9fc6cff487bf7768eb7
- Size of remote file:
- 504 MB
- SHA256:
- a9c7105164f8644330585f2a48af488d7b60b4cb5454cb21dcd8a73291ad90b9
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