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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).


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("ํ ...ํฌ์Šคํ„ฐ๋ณด๊ณ  ์ดˆ๋”ฉ์˜ํ™”์ค„....์˜ค๋ฒ„์—ฐ๊ธฐ์กฐ์ฐจ ๊ฐ€๋ณ์ง€ ์•Š๊ตฌ๋‚˜.")
>>> classifier("์•ก์…˜์ด ์—†๋Š”๋ฐ๋„ ์žฌ๋ฏธ ์žˆ๋Š” ๋ช‡์•ˆ๋˜๋Š” ์˜ํ™”")

[{'label': 'negative', 'score': 0.9642567038536072}]
[{'label': 'positive', 'score': 0.9970554113388062}]
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