Text Classification
Transformers
Safetensors
Korean
electra
ynat-classification
korean_NLP
koELECTRA
Generated from Trainer
Instructions to use Ubin2/ynat_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ubin2/ynat_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ubin2/ynat_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ubin2/ynat_model") model = AutoModelForSequenceClassification.from_pretrained("Ubin2/ynat_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- deb7d816805ae91a2bcb23da48f7ae1356f631c41735edf745b8b5d43d0dd72a
- Size of remote file:
- 5.78 kB
- SHA256:
- f42fe14c82c61bf9529e1232de1d9112b5f2ad2855fa480cacbd502f6e1e8171
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