Text Classification
Transformers
Safetensors
Korean
electra
KoELECTRA
Korean-NLP
topic-classification
news-classification
Generated from Trainer
Instructions to use seoyeon111/ynat-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use seoyeon111/ynat-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="seoyeon111/ynat-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("seoyeon111/ynat-model") model = AutoModelForSequenceClassification.from_pretrained("seoyeon111/ynat-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 62f7f3c52ca18a750bd4506f77b63fa7258cf9a37baca30f505124a37c45ff39
- Size of remote file:
- 5.3 kB
- SHA256:
- fc64119cf5c4828b1f01cdab7b3083fcf7873e0883dc189a9cfaec7a43f3d28b
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