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KoBERT ๋ถ๋ฅ ๋ชจ๋ธ
์ด ๋ชจ๋ธ์ KoBERT๋ฅผ ๊ธฐ๋ฐ์ผ๋ก ํ ์คํธ ๋ถ๋ฅ๋ฅผ ์ํด ํ์ธํ๋๋ ๋ชจ๋ธ์ ๋๋ค.
๋ชจ๋ธ ์ ๋ณด
- ๊ธฐ๋ณธ ๋ชจ๋ธ: beomi/kcbert-base
- ํด๋์ค ์: 12
- ์ฌ์ฉ ๋ฐฉ๋ฒ: ์๋ ์ฝ๋๋ฅผ ์ฐธ์กฐํ์ธ์
์ฌ์ฉ ์์
from transformers import BertForSequenceClassification, BertTokenizer
# ๋ชจ๋ธ๊ณผ ํ ํฌ๋์ด์ ๋ก๋
model_name = "rmsdud/kobert-classifier"
tokenizer = BertTokenizer.from_pretrained(model_name)
model = BertForSequenceClassification.from_pretrained(model_name)
# ์ถ๋ก
text = "๋ถ๋ฅํ ํ
์คํธ๋ฅผ ์
๋ ฅํ์ธ์."
inputs = tokenizer(text, return_tensors="pt", padding=True, truncation=True, max_length=128)
outputs = model(**inputs)
logits = outputs.logits
predicted_class = logits.argmax(-1).item()
print(f"์์ธก ํด๋์ค: predicted_class")
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