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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 405a39e67d647a1f6c7e4ecd871fe0e4d5dbd6de2a8af3fe2aee232509c11799
- Size of remote file:
- 5.3 kB
- SHA256:
- 808a45270821cd4012cd5a0181df897114a9feca5b7003635d5344388dbb888b
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