Instructions to use fabgei/layoutlm-funsd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fabgei/layoutlm-funsd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="fabgei/layoutlm-funsd")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("fabgei/layoutlm-funsd") model = AutoModelForTokenClassification.from_pretrained("fabgei/layoutlm-funsd", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from fabgei/layoutlm-funsd: direct link, hf CLI and curl.
- Browser
- Download file 452 MB
-
https://huggingface.co/fabgei/layoutlm-funsd/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://fabgei/layoutlm-funsd/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/fabgei/layoutlm-funsd/resolve/main/pytorch_model.bin
452 MB
- Xet hash:
- 876dcfbcb250a06a26a6889499db19350b55f9ea0c4a29911390df2d6247387f
- Size of remote file:
- 452 MB
- SHA256:
- fcc11ca585021c8c341a6fa73d00adec1c01f5648ac209053c7bd703593eb521
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