Token Classification
Transformers
PyTorch
English
bert
newspapers
historic
glam
library
nineteenth-century
named entity recognition
ner
toponyms
ocr
Instructions to use Livingwithmachines/toponym-19thC-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Livingwithmachines/toponym-19thC-en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Livingwithmachines/toponym-19thC-en")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Livingwithmachines/toponym-19thC-en") model = AutoModelForTokenClassification.from_pretrained("Livingwithmachines/toponym-19thC-en") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 927c129c646e5e09c9ff89902f7a0e2ad9553303031be8a21e210b7ae1f47a39
- Size of remote file:
- 436 MB
- SHA256:
- b52c97de8d86ff801dd85bed53b171793768e222a266bf81b26535e2289549a9
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