Text Classification
Transformers
Safetensors
Korean
electra
KoELECTRA
Korean-NLP
topic-classification
news-classification
Generated from Trainer
Instructions to use YOUNG7607/ynat-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YOUNG7607/ynat-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="YOUNG7607/ynat-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("YOUNG7607/ynat-model") model = AutoModelForSequenceClassification.from_pretrained("YOUNG7607/ynat-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bebb4a7af4f9955d3dfc63ddee237689cbd006c5d96a609c13d8a728018b5407
- Size of remote file:
- 5.3 kB
- SHA256:
- 6dcbb09860893f1a4a5a2e68d1f33ee019430f39c6f1567025f6cdbc10ba8a05
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