Instructions to use beomus/layoutxlm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use beomus/layoutxlm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="beomus/layoutxlm")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("beomus/layoutxlm") model = AutoModelForTokenClassification.from_pretrained("beomus/layoutxlm") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a0a8c44467ee0b7241da9b7aa33d5c15f27ebbdd6bbb37065e6f4416f2bdb149
- Size of remote file:
- 2.35 kB
- SHA256:
- ec1b31efb6055d76f0abd0efbecf3c5f03ce3044d47367883f089acd09310a68
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.