Instructions to use seppestaes/layoutlm-funsd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use seppestaes/layoutlm-funsd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="seppestaes/layoutlm-funsd")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("seppestaes/layoutlm-funsd") model = AutoModelForTokenClassification.from_pretrained("seppestaes/layoutlm-funsd", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from seppestaes/layoutlm-funsd: direct link, hf CLI and curl.
- Browser
- Download file 451 MB
-
https://huggingface.co/seppestaes/layoutlm-funsd/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://seppestaes/layoutlm-funsd/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/seppestaes/layoutlm-funsd/resolve/main/pytorch_model.bin
451 MB
- Xet hash:
- bee3ae2a9edfb6b85e7db189e301a0d4b076d4ffb166fddf8fc34501d19cfe45
- Size of remote file:
- 451 MB
- SHA256:
- 1d79cc35d713c5056d59dc2d5ada7f71130522a01372c512e33c3b8900b3b086
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.