Instructions to use tanay/layoutlm-custom with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tanay/layoutlm-custom with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="tanay/layoutlm-custom")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("tanay/layoutlm-custom") model = AutoModelForTokenClassification.from_pretrained("tanay/layoutlm-custom") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 26ccf12691ad8ab8cf9bbedf6ec206167fd1d6b565194a58d6ab80796ecb6ba4
- Size of remote file:
- 451 MB
- SHA256:
- cfe8517d27f3933fdf3a7c9d4707cae1acb2a995103c7d51f78e2b8b2682823b
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