Text Classification
Transformers
Safetensors
Korean
electra
KoELECTRA
Korean-NLP
topic-classification
news-classification
Generated from Trainer
Instructions to use ssuhwan/ynat-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ssuhwan/ynat-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ssuhwan/ynat-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ssuhwan/ynat-model") model = AutoModelForSequenceClassification.from_pretrained("ssuhwan/ynat-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 766d2cd4e3884941ac989430f3a3d341c091bcdf0685dfbd8df1656305215f1b
- Size of remote file:
- 5.47 kB
- SHA256:
- fdfb25c612f872bfa4cdcdae87987016b4389a8b4ca9ba67e3d6d254289b38e9
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