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 training_args.bin from fabgei/layoutlm-funsd: direct link, hf CLI and curl.
- Browser
- Download file 3.58 kB
-
https://huggingface.co/fabgei/layoutlm-funsd/resolve/main/training_args.bin
- Command line
-
hf download hf://fabgei/layoutlm-funsd/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/fabgei/layoutlm-funsd/resolve/main/training_args.bin
3.58 kB
- Xet hash:
- 2a5bd096c841f92cafbc498ce50f67548ba34b48d99afafc53aeed43877f5ddb
- Size of remote file:
- 3.58 kB
- SHA256:
- 52583ebc0195bd6a30b79d88b9204800e7ae0dd59ac86f3bf8af30d44b765a3e
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