Instructions to use omarelsayeed/testing_layoutlm2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use omarelsayeed/testing_layoutlm2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="omarelsayeed/testing_layoutlm2")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("omarelsayeed/testing_layoutlm2") model = AutoModelForTokenClassification.from_pretrained("omarelsayeed/testing_layoutlm2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 657250061abd09af8acff56a914926405a5e26e763d6c2c063166ea042e126b5
- Size of remote file:
- 1.43 GB
- SHA256:
- 97a8ed9c27448730868af7dc2122a48cbe986672ef9b809056869f75a1d1319f
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