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νκ΅μΈ μ΄λ¦ μΈμ λͺ¨λΈ
kor-bert fine-tuning λͺ¨λΈ
μμ£Ό μμ°λ νκΈμ΄λ¦ κΈ°μ€μΌλ‘ μμ±κΈ°λ₯Ό λ§λ€μ΄μ, 16λ§κ°μ νκΈ μ΄λ¦μ μμ± ν νμ΅ν λͺ¨λΈμ λλ€.
ex) μλ νμΈμ. μμ€μμ λλ€. -> μλ νμΈμ. ***μ λλ€.
from transformers import BertTokenizerFast, BertForTokenClassification
from transformers import pipeline
model_name = 'joon09/kor-naver-ner-name'
tokenizer = BertTokenizerFast.from_pretrained(model_name)
model = BertForTokenClassification.from_pretrained(model_name)
nlp = pipeline("ner", model=model, tokenizer=tokenizer)
ner('μλ
νμΈμ. μμ€μμ
λλ€.',grouped_entities=True,aggregation_strategy='average')
[{'entity_group': 'PER',
'score': 0.99999785,
'word': 'μ',
'start': 7,
'end': 8},
{'entity_group': 'PER',
'score': 0.82035744,
'word': '##μ€μ',
'start': 8,
'end': 10}]
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