Text Classification
Transformers
Safetensors
Korean
electra
KoELECTRA
Korean-NLP
topic-classification
news-classification
Generated from Trainer
Instructions to use joaram/ynat-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use joaram/ynat-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="joaram/ynat-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("joaram/ynat-model") model = AutoModelForSequenceClassification.from_pretrained("joaram/ynat-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f6eb26b8614c2783c7e0d0ed4223a28717e1e5cb396fd7a1ebdff570b68cb211
- Size of remote file:
- 5.84 kB
- SHA256:
- a649cd35f744f2ec1152f134aaf54377eeb650bca4170c8a5207576690958bf0
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