Text Classification
Transformers
Safetensors
Korean
electra
KoELECTRA
Korean-NLP
topic-classification
news-classification
Generated from Trainer
Instructions to use KRseong/ynat-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KRseong/ynat-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="KRseong/ynat-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("KRseong/ynat-model") model = AutoModelForSequenceClassification.from_pretrained("KRseong/ynat-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a6487e04c2d7178b54826ffafe70544fd99b949bb2a84228d9b0020fb9689a1b
- Size of remote file:
- 5.37 kB
- SHA256:
- da15856a4b0714155a148431a2120a8732497f28a249627cbcf5129c1cb8f6e3
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