Instructions to use wldn/korean-text-classification-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wldn/korean-text-classification-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wldn/korean-text-classification-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wldn/korean-text-classification-model") model = AutoModelForSequenceClassification.from_pretrained("wldn/korean-text-classification-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Korean Text Classification Model
Base model: beomi/KcELECTRA-base
This model was fine-tuned with Hugging Face Transformers Trainer.
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Inference Example
from transformers import pipeline
repo_id = "YOUR_USERNAME/YOUR_REPO_NAME"
classifier = pipeline( "text-classification", model=repo_id, tokenizer=repo_id )
classifier("여기에 분류할 문장을 입력하세요.")
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Model tree for wldn/korean-text-classification-model
Base model
beomi/KcELECTRA-base