Instructions to use Iclal/layoutlm-funsd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Iclal/layoutlm-funsd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Iclal/layoutlm-funsd")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Iclal/layoutlm-funsd") model = AutoModelForTokenClassification.from_pretrained("Iclal/layoutlm-funsd", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Iclal/layoutlm-funsd: direct link, hf CLI and curl.
- Browser
- Download file 3.52 kB
-
https://huggingface.co/Iclal/layoutlm-funsd/resolve/main/training_args.bin
- Command line
-
hf download hf://Iclal/layoutlm-funsd/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Iclal/layoutlm-funsd/resolve/main/training_args.bin
3.52 kB
- Xet hash:
- 3b14a12fd1824ec988b2fbe30b1783380af4f8bf1b132f8f67283444f191b59d
- Size of remote file:
- 3.52 kB
- SHA256:
- 0702e63d62e90d43d6432d36cde1a9e9f910d3deb54b5fd3889983f6e067aab2
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