BERT multilingual basecased finetuned with NSMC
This model is a fine-tune checkpoint of bert-base-multilingual-cased, fine-tuned on NSMC(Naver Sentiment Movie Corpus).
Usage
You can use this model directly with a pipeline for sentiment-analysis:
>>> from transformers import pipeline
>>> classifier = pipeline(
"sentiment-analysis", model="sangrimlee/bert-base-multilingual-cased-nsmc"
)
>>> classifier("ํ ...ํฌ์คํฐ๋ณด๊ณ ์ด๋ฉ์ํ์ค....์ค๋ฒ์ฐ๊ธฐ์กฐ์ฐจ ๊ฐ๋ณ์ง ์๊ตฌ๋.")
>>> classifier("์ก์
์ด ์๋๋ฐ๋ ์ฌ๋ฏธ ์๋ ๋ช์๋๋ ์ํ")
[{'label': 'negative', 'score': 0.9642567038536072}]
[{'label': 'positive', 'score': 0.9970554113388062}]
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