Create README.md

README.md

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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 bi-encoder.
+This model structure is as same as [tuhailong/cross_encoder_roberta-wwm-ext_v1](https://huggingface.co/tuhailong/cross_encoder_roberta-wwm-ext_v1)，the difference is changing the epoch from 5 to 1, the performance is better in my dataset.
+
+### 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])
+```