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:
- 64a7d734901784fbefc9d7b9f18a9996db62d602077ba8138b7c243ba20127f3
- Size of remote file:
- 3.64 kB
- SHA256:
- 3d3d13857b5608ae402b9d92ee2503fd6f1070f2d3e4f8968c1f99903a2daba6
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