Token Classification
Flair
PyTorch
Latin
sequence-tagger-model
named-entity-recognition
legal-history
medieval-latin
early-modern
ius-commune
citations
digital-humanities
Eval Results (legacy)
Instructions to use mschonhardt/ius-commune-citations-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Flair
How to use mschonhardt/ius-commune-citations-ner with Flair:
from flair.data import Sentence from flair.models import SequenceTagger tagger = SequenceTagger.load("mschonhardt/ius-commune-citations-ner") sentence = Sentence("George Washington went to Washington.") tagger.predict(sentence) print(sentence) - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from mschonhardt/ius-commune-citations-ner: direct link, hf CLI and curl.
- Browser
- Download file 2.67 GB
-
https://huggingface.co/mschonhardt/ius-commune-citations-ner/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://mschonhardt/ius-commune-citations-ner/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/mschonhardt/ius-commune-citations-ner/resolve/main/pytorch_model.bin
2.67 GB
- Xet hash:
- d58afd2382431347cf0ac8863740296c40942ee9a758f47e944a77e26d224e8c
- Size of remote file:
- 2.67 GB
- SHA256:
- c6eec4ba2599880a4fdab01ff21d97e47da5a07ebd53f922440a87a6035b2446
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