Create README.md

README.md

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+---
+language:
+- ko
+---
+pipeline_tag: sentence-similarity
+tags:
+- sentence-transformers
+- sentence-similarity
+- transformers
+---
+
+# leewaay/kpf-bert-base-klueSTS-cross
+
+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.
+
+## Usage (Sentence-Transformers)
+
+Using this model becomes easy when you have [sentence-transformers](https://www.SBERT.net) installed:
+
+```bash
+pip install -U sentence-transformers
+```
+
+Then you can use the model like this:
+
+```python
+from sentence_transformers import CrossEncoder
+pairs = [('Query', 'Paragraph1'), ('Query', 'Paragraph2') , ('Query', 'Paragraph3')]
+
+model = CrossEncoder('leewaay/kpf-bert-base-klueSTS-cross')
+scores = model.predict(pairs)
+print(scores)
+```
+
+## Citing & Authors
+
+[Wonseok Lee](https://github.com/leewaay)