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")# pip install -U transformers accelerate # 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
Download tokenizer.json from scales-okn/ner-entry-date-section: direct link, hf CLI and curl.
- Browser
- Download file 8.65 MB
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https://huggingface.co/scales-okn/ner-entry-date-section/resolve/main/tokenizer.json
- Command line
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hf download hf://scales-okn/ner-entry-date-section/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/scales-okn/ner-entry-date-section/resolve/main/tokenizer.json
8.65 MB
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