Instructions to use dodogigi/layoutlm-funsd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dodogigi/layoutlm-funsd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="dodogigi/layoutlm-funsd")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("dodogigi/layoutlm-funsd") model = AutoModelForTokenClassification.from_pretrained("dodogigi/layoutlm-funsd", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from dodogigi/layoutlm-funsd: direct link, hf CLI and curl.
- Browser
- Download file 451 MB
-
https://huggingface.co/dodogigi/layoutlm-funsd/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://dodogigi/layoutlm-funsd/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/dodogigi/layoutlm-funsd/resolve/main/pytorch_model.bin
451 MB
- Xet hash:
- 9f9f8e6543a5fba075f9d4b280685dbee780adbf266c591f3cca7e727222ee2e
- Size of remote file:
- 451 MB
- SHA256:
- acbb91558bfbc31d513e862dcf1f8b041f31753630dec8c118f5fa6c2ded073f
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