Text Classification
Transformers
Safetensors
Korean
electra
KoELECTRA
Korean-NLP
topic-classification
news-classification
Generated from Trainer
Instructions to use wodnd9923/ynat-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wodnd9923/ynat-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wodnd9923/ynat-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wodnd9923/ynat-model") model = AutoModelForSequenceClassification.from_pretrained("wodnd9923/ynat-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f0a1210839f58bec50e9a0e9fee5632fcc8108ed59876f7ce25d4c18ad696f36
- Size of remote file:
- 5.41 kB
- SHA256:
- c2d81e0c73ca30e70b2562f1be25e3d5698c3535d272d44f108465e66f48971f
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