Instructions to use pmorelr/layoutlm-doclaynet-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pmorelr/layoutlm-doclaynet-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="pmorelr/layoutlm-doclaynet-test")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("pmorelr/layoutlm-doclaynet-test") model = AutoModelForTokenClassification.from_pretrained("pmorelr/layoutlm-doclaynet-test") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 60e548cc5315bc46aca56c5600115a1d63ac046f71bddc53acbc32bcffe538dd
- Size of remote file:
- 451 MB
- SHA256:
- 5364d36cc99f61aa4c61f0e8a87d9b4f237953b2e346834b1cd131573fad3cb7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.