Instructions to use mdecot/RobotDocNLP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mdecot/RobotDocNLP with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mdecot/RobotDocNLP")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mdecot/RobotDocNLP") model = AutoModelForTokenClassification.from_pretrained("mdecot/RobotDocNLP", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1b010ead42a2fd8acc74eb3328a85a70100a25beaf141f7a49c3e0dd230befac
- Size of remote file:
- 437 MB
- SHA256:
- 7503b4cd742080e66cabed57a38d2a0e0f07fc301c722e650b7794cbfbb0af4e
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