Text Classification
Transformers
Safetensors
Korean
electra
KoELECTRA
Korean-NLP
topic-classification
news-classification
Generated from Trainer
Instructions to use eyeons/ynat-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eyeons/ynat-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="eyeons/ynat-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("eyeons/ynat-model") model = AutoModelForSequenceClassification.from_pretrained("eyeons/ynat-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 217029797a2cf4887df4edad0cd9c06cff591435e71d52a85af2b303f2209253
- Size of remote file:
- 452 MB
- SHA256:
- 7649919739763cf9fc276dda07db91cfdbb059613eb482fc30fcd47c3fc61a0d
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