Instructions to use scales-okn/ner-entry-date-section with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use scales-okn/ner-entry-date-section with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="scales-okn/ner-entry-date-section")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("scales-okn/ner-entry-date-section") model = AutoModelForTokenClassification.from_pretrained("scales-okn/ner-entry-date-section", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cfd53d961b41e5b48c34c88ccfb13a56ebb2ccdffa5f9fec32c7e63d19ec8b9b
- Size of remote file:
- 1.74 GB
- SHA256:
- 3744edd4f1f0005d9ef629e271ff9c04859fcd3f67e0a410f2d587b11e4e2e92
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