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:
- 387e74778f813381684210d5250f88dc5991b7f15de76734cb6a35f8ca39f9a1
- Size of remote file:
- 3.25 kB
- SHA256:
- 8490f456da67de689f351ecc50cd6c728b7f5c9d26051264649edd355ee5f328
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