Text Classification
Transformers
Safetensors
Korean
electra
KoELECTRA
Korean-NLP
topic-classification
news-classification
Generated from Trainer
Instructions to use YOUNG7607/ynat-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YOUNG7607/ynat-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="YOUNG7607/ynat-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("YOUNG7607/ynat-model") model = AutoModelForSequenceClassification.from_pretrained("YOUNG7607/ynat-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 58b6c6148441d9b2086718d7e52be9dd543ba2b94e0189d447487b41e891af52
- Size of remote file:
- 452 MB
- SHA256:
- f58d5d06b078f7b38cdbabdc262367982257231c216443343e7a94e4d0600892
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