Instructions to use marcodifelice/layoutlm-funsd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use marcodifelice/layoutlm-funsd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="marcodifelice/layoutlm-funsd")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("marcodifelice/layoutlm-funsd") model = AutoModelForTokenClassification.from_pretrained("marcodifelice/layoutlm-funsd", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from marcodifelice/layoutlm-funsd: direct link, hf CLI and curl.
- Browser
- Download file 3.57 kB
-
https://huggingface.co/marcodifelice/layoutlm-funsd/resolve/main/training_args.bin
- Command line
-
hf download hf://marcodifelice/layoutlm-funsd/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/marcodifelice/layoutlm-funsd/resolve/main/training_args.bin
3.57 kB
- Xet hash:
- 6faf388f1fbbdd2c0907893916b8d320c69b5de7218cc578c843cb56bf41226c
- Size of remote file:
- 3.57 kB
- SHA256:
- 202aaebcf07642643933b45fe3834287def3afee33094808b7e00b3ea5573d6e
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