Text Classification
Transformers
Safetensors
Korean
electra
KoELECTRA
Korean-NLP
topic-classification
news-classification
Generated from Trainer
Instructions to use koreanboy/ynat-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use koreanboy/ynat-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="koreanboy/ynat-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("koreanboy/ynat-model") model = AutoModelForSequenceClassification.from_pretrained("koreanboy/ynat-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d2af6b92eb1bc427c4673cfa2ecc03d94842e33da9368b61df1c270fe6ebc62e
- Size of remote file:
- 452 MB
- SHA256:
- 62c01931e6f47e1cebbb1ab2b9a4a0eb080264485c62f6b02367c35335217ae4
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