Text Classification
Transformers
PyTorch
Safetensors
Korean
English
xlm-roberta
text-embeddings-inference
Instructions to use Dongjin-kr/ko-reranker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Dongjin-kr/ko-reranker with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Dongjin-kr/ko-reranker")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Dongjin-kr/ko-reranker") model = AutoModelForSequenceClassification.from_pretrained("Dongjin-kr/ko-reranker", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 559f16f056950a19c48d9e3e7106da6429be5e33d30f1b424a26c2a2ae293f66
- Size of remote file:
- 17.1 MB
- SHA256:
- f06b6596a5580f8e916d027ecfdaac660c3112f95fa23106d35851d5ee51654d
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