Text Classification
Transformers
Safetensors
Korean
electra
KoELECTRA
Korean-NLP
topic-classification
news-classification
Generated from Trainer
Instructions to use Son1001/ynat-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Son1001/ynat-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Son1001/ynat-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Son1001/ynat-model") model = AutoModelForSequenceClassification.from_pretrained("Son1001/ynat-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c96e14e83369c287a765c4abb80f9005fcde1ab352e4fc0e7d5ecda6f75011a7
- Size of remote file:
- 5.37 kB
- SHA256:
- 808d058107892206d3ba4cb5d936ae416c235874c1f90bd89cda712d75fb5911
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