Text Classification
Transformers
Safetensors
Korean
electra
KoELECTRA
Korean-NLP
topic-classification
news-classification
Generated from Trainer
Instructions to use gyu8/ynat-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gyu8/ynat-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gyu8/ynat-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gyu8/ynat-model") model = AutoModelForSequenceClassification.from_pretrained("gyu8/ynat-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 84adbaa5aa41eb5a7e744a4e06d0dbcbdd64493cf9e981c915adbb481c6ff4b3
- Size of remote file:
- 5.3 kB
- SHA256:
- 9f27b41bed4991b98b84b1ae4c8f8c7bf151a001a01282be8a205701d7268d94
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