Text Classification
Transformers
Safetensors
Korean
electra
KoELECTRA
Korean-NLP
topic-classification
news-classification
Generated from Trainer
Instructions to use heejinoh/ynat-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use heejinoh/ynat-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="heejinoh/ynat-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("heejinoh/ynat-model") model = AutoModelForSequenceClassification.from_pretrained("heejinoh/ynat-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5ff95a2da94f82269b45d5fb3d3bbb57b0c5c17a5ef1e86cf5935fcf58a0ce97
- Size of remote file:
- 452 MB
- SHA256:
- 5b2b46f6b13ea3032f44aaac40a1e24e4f8a7348bb477a81b64f7dc680d90ae4
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