Instructions to use MonkeeZhang/layoutlmv3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MonkeeZhang/layoutlmv3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="MonkeeZhang/layoutlmv3")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("MonkeeZhang/layoutlmv3") model = AutoModelForTokenClassification.from_pretrained("MonkeeZhang/layoutlmv3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from MonkeeZhang/layoutlmv3: direct link, hf CLI and curl.
- Browser
- Download file 9.1 MB
-
https://huggingface.co/MonkeeZhang/layoutlmv3/resolve/refs%2Fpr%2F1/tokenizer.json
- Command line
-
hf download hf://MonkeeZhang/layoutlmv3@refs/pr/1/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/MonkeeZhang/layoutlmv3/resolve/refs%2Fpr%2F1/tokenizer.json
9.1 MB
File too large to display, you can check the raw version instead.