Text Classification
Transformers
ONNX
Safetensors
Korean
bert
korean
kcbert
profanity
hate-speech
toxicity
Eval Results (legacy)
text-embeddings-inference
Instructions to use illimax/kcbert-NEMO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use illimax/kcbert-NEMO with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="illimax/kcbert-NEMO")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("illimax/kcbert-NEMO") model = AutoModelForSequenceClassification.from_pretrained("illimax/kcbert-NEMO", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Add ONNX weights for transformers.js
Browse files- onnx/model.onnx +3 -0
- onnx/model_quantized.onnx +3 -0
onnx/model.onnx
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