Instructions to use wldn/korean-text-classification-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wldn/korean-text-classification-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wldn/korean-text-classification-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wldn/korean-text-classification-model") model = AutoModelForSequenceClassification.from_pretrained("wldn/korean-text-classification-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 31219aabf1d05927feafd9d5223327651ba4de3ec9e298a49b617fd252a5badc
- Size of remote file:
- 5.2 kB
- SHA256:
- 5975031e9a55ef7a5b6848abff9566ee479c4c4f04150c2b200fe1bdecf97677
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