Instructions to use hun3359/mdistilbertV3.1-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hun3359/mdistilbertV3.1-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hun3359/mdistilbertV3.1-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hun3359/mdistilbertV3.1-sentiment") model = AutoModelForSequenceClassification.from_pretrained("hun3359/mdistilbertV3.1-sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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# 한국어 감정 분류모델
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## 60가지의 세분화된 감정분류 모델
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### Dataset: Aihub-감성대화말뭉치
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### Dataset URL : https://aihub.or.kr/aihubdata/data/view.do?currMenu=115&topMenu=100&aihubDataSe=realm&dataSetSn=86
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# 한국어 감정 분류모델
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# Korean Sentiment Classification Model
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## 60가지의 세분화된 감정분류 모델
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### Dataset: Aihub-감성대화말뭉치
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### Dataset URL : https://aihub.or.kr/aihubdata/data/view.do?currMenu=115&topMenu=100&aihubDataSe=realm&dataSetSn=86
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