Text Classification
Transformers
Safetensors
Korean
electra
KoELECTRA
Korean-NLP
topic-classification
news-classification
Generated from Trainer
Instructions to use ykm5922/ynat-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ykm5922/ynat-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ykm5922/ynat-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ykm5922/ynat-model") model = AutoModelForSequenceClassification.from_pretrained("ykm5922/ynat-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c9ef62516638adda546237bada8d6956bb50a17095d714e9eedc4849b3e45a16
- Size of remote file:
- 5.37 kB
- SHA256:
- 40fb841eaebbf7f4a6780427774fa07b3740b50f3e243711c90ceb8db2c4eae5
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