Text Classification
Transformers
Safetensors
Korean
electra
korean_NLP
KoELECTRA
Generated from Trainer
Instructions to use depos/ynat_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use depos/ynat_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="depos/ynat_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("depos/ynat_model") model = AutoModelForSequenceClassification.from_pretrained("depos/ynat_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c30204e4770380c72d74d5068b175dc00acc8b0d79ff983d957a7a9e128f58f2
- Size of remote file:
- 5.78 kB
- SHA256:
- 81605f6babca17c19c3d050f53dcecf80e9e5115f77a3a6130b5e69d3452caac
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