Instructions to use dell-research-harvard/historical_newspaper_ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dell-research-harvard/historical_newspaper_ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="dell-research-harvard/historical_newspaper_ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("dell-research-harvard/historical_newspaper_ner") model = AutoModelForTokenClassification.from_pretrained("dell-research-harvard/historical_newspaper_ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 767d561b441dde50cc8336ee62e2fc9c2027bd25ed31bb26b6ba0e79fcf91d0b
- Size of remote file:
- 1.42 GB
- SHA256:
- 63ab29dd93dddd1b37c226039e615efb52f04c67561fe7ebfdc5aed49f934eb2
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