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:
- e49f2529a2b94dc0ffc630456e210ca4d3340a6426d70c1dac365755ad3dae8d
- Size of remote file:
- 3.5 kB
- SHA256:
- 2532c628f8b895d1f396a8de18bdc751c9d0b18f627ab3fdfe67ce25f0740634
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.