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meddocan-flair-we-lstm-crf
GuiGel/meddocan-flair-we-lstm-crf
meddocan-flair-we-lstm-crf is a token classification model from GuiGel. Use it when you need labels on individual words, such as names. It is set up for flair.
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At a glance
- Task
- Token Classification
- Library
- flair
- Access
- Public
- Created
- Nov 7, 2022
- Updated
- Nov 7, 2022
- SHA
- da6b4030
Try a prompt
Model card
From the Hugging Face model README
Demo: How to use in Flair
Requires:
- Flair (
pip install flair)
from flair.data import Sentence
from flair.models import SequenceTagger
# load tagger
tagger = SequenceTagger.load("GuiGel/meddocan-flair-we-lstm-crf")
# make example sentence
sentence = Sentence("On September 1st George won 1 dollar while watching Game of Thrones.")
# predict NER tags
tagger.predict(sentence)
# print sentence
print(sentence)
# print predicted NER spans
print('The following NER tags are found:')
# iterate over entities and print
for entity in sentence.get_spans('ner'):
print(entity)
- Task
- Token Classification
- Library
- flair
- Created
- Nov 7, 2022
- Updated
- Nov 7, 2022