Instructions to use matthewburke/korean_sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use matthewburke/korean_sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="matthewburke/korean_sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("matthewburke/korean_sentiment") model = AutoModelForSequenceClassification.from_pretrained("matthewburke/korean_sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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```
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from transformers import pipeline
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is_positive = preds[0][1]['score'] > 0.5
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```
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```
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from transformers import pipeline
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classifier = pipeline("sentiment-analysis")
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classifier("์ธ๋ํ๋ค. ๊ฐ์ด์ ๋น์๊ฐ ๋ ์์ ํ๋ค.")
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```
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