Text Classification
Transformers
Safetensors
Korean
electra
KoELECTRA
Korean-NLP
topic-classification
news-classification
Generated from Trainer
Instructions to use hyeon7897/ynat-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hyeon7897/ynat-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hyeon7897/ynat-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hyeon7897/ynat-model") model = AutoModelForSequenceClassification.from_pretrained("hyeon7897/ynat-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f42b0b0758d1464298d0020675ff1b9fb53e85bcc6872ec15570dfe98b52fc12
- Size of remote file:
- 5.3 kB
- SHA256:
- 57f6b6024ecb086a1b5c46b186bcb249143930aed54b660a51200051c8abf8ba
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