Token Classification
Transformers
Safetensors
layoutlmv3
Generated from Trainer
Eval Results (legacy)
Instructions to use ritutweets46/Layoutlmv3-finetuned-DocLayNet-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ritutweets46/Layoutlmv3-finetuned-DocLayNet-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ritutweets46/Layoutlmv3-finetuned-DocLayNet-test")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("ritutweets46/Layoutlmv3-finetuned-DocLayNet-test") model = AutoModelForTokenClassification.from_pretrained("ritutweets46/Layoutlmv3-finetuned-DocLayNet-test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from ritutweets46/Layoutlmv3-finetuned-DocLayNet-test: direct link, hf CLI and curl.
- Browser
- Download file 2.11 MB
-
https://huggingface.co/ritutweets46/Layoutlmv3-finetuned-DocLayNet-test/resolve/main/tokenizer.json
- Command line
-
hf download hf://ritutweets46/Layoutlmv3-finetuned-DocLayNet-test/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/ritutweets46/Layoutlmv3-finetuned-DocLayNet-test/resolve/main/tokenizer.json
2.11 MB
File too large to display, you can check the raw version instead.