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# Import generic wrappers
from transformers import AutoModel, AutoTokenizer
if __name__ == "__main__":
from flair.data import Sentence
from flair.models import SequenceTagger
# load tagger
tagger = SequenceTagger.load("flair/ner-english-large")
# make example sentence
sentence = Sentence("George Washington went to Washington")
# 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)
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