Instructions to use katanaml/layoutlmv2-finetuned-cord with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use katanaml/layoutlmv2-finetuned-cord with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="katanaml/layoutlmv2-finetuned-cord")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("katanaml/layoutlmv2-finetuned-cord") model = AutoModelForTokenClassification.from_pretrained("katanaml/layoutlmv2-finetuned-cord") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3aa5c4fc2b285983866684834ad3a5ef6b1f83e04214ccac49435dc82c029e98
- Size of remote file:
- 3.06 kB
- SHA256:
- 1141522f268e0a3439b105b21dbe76211abaca81aa2507d6d1c03ca0487e284a
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