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---
language: zh
tags:
- cross-encoder
datasets:
- dialogue
---
# Data
train data is similarity sentence data from E-commerce dialogue, about 50w sentence pairs.
## Model
model created by [sentence-tansformers](https://www.sbert.net/index.html)，model struct is cross-encoder，pretrained model is hfl/chinese-roberta-wwm-ext-large.
### Code
train code from https://github.com/TTurn/cross-encoder
#### Usage
```python
>>> from sentence_transformers.cross_encoder import CrossEncoder
>>> model = CrossEncoder(model_save_path, device="cuda", max_length=64)
>>> sentences = ["今天天气不错", "今天心情不错"]
>>> score = model.predict([sentences])
>>> print(score[0])
``` |