Text Classification
Transformers
Safetensors
Korean
electra
koELECTRA
Korean-NLP
topic-classification
news-classification
Generated from Trainer
Instructions to use djun604/ynet-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use djun604/ynet-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="djun604/ynet-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("djun604/ynet-model") model = AutoModelForSequenceClassification.from_pretrained("djun604/ynet-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 32690639cc8c8e4db1552edf703a96bb978578717d0a8f0eb3fbe8f518f8f340
- Size of remote file:
- 5.3 kB
- SHA256:
- 0856d836faccac23f975a97525007645023bb6b02808c75203086ae632c926e4
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