Instructions to use Kwan0/layoutlmv3-base-finetune-DocLayNet-100k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kwan0/layoutlmv3-base-finetune-DocLayNet-100k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Kwan0/layoutlmv3-base-finetune-DocLayNet-100k")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("Kwan0/layoutlmv3-base-finetune-DocLayNet-100k") model = AutoModelForTokenClassification.from_pretrained("Kwan0/layoutlmv3-base-finetune-DocLayNet-100k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Kwan0/layoutlmv3-base-finetune-DocLayNet-100k: direct link, hf CLI and curl.
- Browser
- Download file 2.11 MB
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https://huggingface.co/Kwan0/layoutlmv3-base-finetune-DocLayNet-100k/resolve/main/tokenizer.json
- Command line
-
hf download hf://Kwan0/layoutlmv3-base-finetune-DocLayNet-100k/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/Kwan0/layoutlmv3-base-finetune-DocLayNet-100k/resolve/main/tokenizer.json
2.11 MB
File too large to display, you can check the raw version instead.