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--- |
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pipeline_tag: sentence-similarity |
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tags: |
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- sentence-transformers |
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- sentence-similarity |
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- transformers |
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language: |
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- ko |
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--- |
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# leewaay/kpf-bert-base-klueSTS-cross |
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This is a [sentence-transformers](https://www.SBERT.net) model: A cross encoder trained with the pretrained [`jinmang2/kpfbert`](https://huggingface.co./jinmang2/kpfbert) model on the [KLUE STS dataset](https://huggingface.co./datasets/klue#sts) for sentence similarity tasks. It's specifically designed for direct evaluation of sentence pairs, making it highly effective for [Re-Ranking](https://www.sbert.net/examples/applications/retrieve_rerank/README.html) and [Augmented SBERT](https://www.sbert.net/examples/training/data_augmentation/README.html) for data labeling tasks aimed at enhancing SBERT. |
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## Usage (Sentence-Transformers) |
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Using this model becomes easy when you have [sentence-transformers](https://www.SBERT.net) installed: |
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```bash |
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pip install -U sentence-transformers |
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``` |
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Then you can use the model like this: |
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```python |
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from sentence_transformers import CrossEncoder |
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pairs = [('Query', 'Paragraph1'), ('Query', 'Paragraph2') , ('Query', 'Paragraph3')] |
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model = CrossEncoder('leewaay/kpf-bert-base-klueSTS-cross') |
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scores = model.predict(pairs) |
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print(scores) |
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``` |
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## Citing & Authors |
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[Wonseok Lee](https://github.com/leewaay) |
