Token Classification
Transformers
Safetensors
layoutlmv3
Generated from Trainer
Eval Results (legacy)
Instructions to use EslamAhmed/LayoutLMv3-DocLayNet-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EslamAhmed/LayoutLMv3-DocLayNet-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="EslamAhmed/LayoutLMv3-DocLayNet-small")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("EslamAhmed/LayoutLMv3-DocLayNet-small") model = AutoModelForTokenClassification.from_pretrained("EslamAhmed/LayoutLMv3-DocLayNet-small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from EslamAhmed/LayoutLMv3-DocLayNet-small: direct link, hf CLI and curl.
- Browser
- Download file 5.37 kB
-
https://huggingface.co/EslamAhmed/LayoutLMv3-DocLayNet-small/resolve/main/training_args.bin
- Command line
-
hf download hf://EslamAhmed/LayoutLMv3-DocLayNet-small/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/EslamAhmed/LayoutLMv3-DocLayNet-small/resolve/main/training_args.bin
5.37 kB
- Xet hash:
- 884dfb545c284940086c9eb5659e7127f20948b4f5a2d8e50a410e890ba8bbd4
- Size of remote file:
- 5.37 kB
- SHA256:
- 677a1469c1d9d6d796962a71656d5a3d10df9255e2eb8c646617f6c894b5bc82
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