Instructions to use Wikidepia/SB-AutoSegment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Flair
How to use Wikidepia/SB-AutoSegment with Flair:
from flair.data import Sentence from flair.models import SequenceTagger tagger = SequenceTagger.load("Wikidepia/SB-AutoSegment") sentence = Sentence("George Washington went to Washington.") tagger.predict(sentence) print(sentence) - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Wikidepia/SB-AutoSegment: direct link, hf CLI and curl.
- Browser
- Download file 134 MB
-
https://huggingface.co/Wikidepia/SB-AutoSegment/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Wikidepia/SB-AutoSegment/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Wikidepia/SB-AutoSegment/resolve/main/pytorch_model.bin
134 MB
- Xet hash:
- a32e496caf2aaabf3913ddb524f74cc8c486bed427bb138b2839bd9d5f664431
- Size of remote file:
- 134 MB
- SHA256:
- b4bb7065ae6c88e72a25f1171a616c68fc4dd39122db0727f2741e6ecadf1287
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