| language: zh | |
| tags: | |
| - sbert | |
| datasets: | |
| - dialogue | |
| library_name: sentence-transformers | |
| pipeline_tag: text-ranking | |
| # Data | |
| train data is similarity sentence data from E-commerce dialogue, about 20w sentence pairs. | |
| ## Model | |
| model created by [sentence-tansformers](https://www.sbert.net/index.html)，model struct is cross-encoder | |
| ### Usage | |
| ```python | |
| >>> from sentence_transformers.cross_encoder import CrossEncoder | |
| >>> model = CrossEncoder('tuhailong/cross-encoder') | |
| >>> scores = model.predict([["今天天气不错", "今天心情不错"]]) | |
| >>> print(scores) | |
| ``` |