Instructions to use functionX86/layoutlmv3-finetuned-cordv2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use functionX86/layoutlmv3-finetuned-cordv2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="functionX86/layoutlmv3-finetuned-cordv2")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("functionX86/layoutlmv3-finetuned-cordv2") model = AutoModelForTokenClassification.from_pretrained("functionX86/layoutlmv3-finetuned-cordv2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from functionX86/layoutlmv3-finetuned-cordv2: direct link, hf CLI and curl.
- Browser
- Download file 2.11 MB
-
https://huggingface.co/functionX86/layoutlmv3-finetuned-cordv2/resolve/main/tokenizer.json
- Command line
-
hf download hf://functionX86/layoutlmv3-finetuned-cordv2/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/functionX86/layoutlmv3-finetuned-cordv2/resolve/main/tokenizer.json
2.11 MB
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