Instructions to use mdarhri00/named-entity-recognition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mdarhri00/named-entity-recognition with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mdarhri00/named-entity-recognition")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mdarhri00/named-entity-recognition") model = AutoModelForTokenClassification.from_pretrained("mdarhri00/named-entity-recognition") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e13ad1ba8820c5ea11c62f14fefb5f7fe5305473756826d04e84394f39989df4
- Size of remote file:
- 709 MB
- SHA256:
- 985fcceb62b1be6e40a5dcca2789694fe6f933ca310591b852f6a074479f4b5a
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