Instructions to use ManelR/layoutlm-funsd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ManelR/layoutlm-funsd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ManelR/layoutlm-funsd")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ManelR/layoutlm-funsd") model = AutoModelForTokenClassification.from_pretrained("ManelR/layoutlm-funsd", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ManelR/layoutlm-funsd: direct link, hf CLI and curl.
- Browser
- Download file 3.58 kB
-
https://huggingface.co/ManelR/layoutlm-funsd/resolve/main/training_args.bin
- Command line
-
hf download hf://ManelR/layoutlm-funsd/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ManelR/layoutlm-funsd/resolve/main/training_args.bin
3.58 kB
- Xet hash:
- c498064d59a47bfbbe56b4eaa26e1ce1eb2d77a54e7e6674f5bae13c6684a21b
- Size of remote file:
- 3.58 kB
- SHA256:
- fbbffb02425cd056d1e34c35fdf46ca8e5bae77bc2ccca44bd387f08d27f0fc9
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