Instructions to use ritutweets46/layoutlm-funsd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ritutweets46/layoutlm-funsd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ritutweets46/layoutlm-funsd")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ritutweets46/layoutlm-funsd") model = AutoModelForTokenClassification.from_pretrained("ritutweets46/layoutlm-funsd", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ritutweets46/layoutlm-funsd: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/ritutweets46/layoutlm-funsd/resolve/main/training_args.bin
- Command line
-
hf download hf://ritutweets46/layoutlm-funsd/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ritutweets46/layoutlm-funsd/resolve/main/training_args.bin
4.92 kB
- Xet hash:
- 8f01691e7b1eb3bf8d98e23250dc4b0a000a4ceb23997fe90e40d8a01f46adc8
- Size of remote file:
- 4.92 kB
- SHA256:
- 47bfe7f8bfc58ed7641d2e3b0fdafb0aef4df48fe0b37fb29623657dff8e128f
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