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---
language: zh
tags:
- simcse
datasets:
- dialogue
---
# Data
train data is similarity sentence data from E-commerce dialogue
## Model
model created by [sentence-tansformers](https://www.sbert.net/index.html)，model struct is cross-encoder
### Usage
```python
>>> from transformers import AutoTokenizer, AutoModel
>>> model = AutoModel.from_pretrained("tuhailong/simcse_model")
>>> tokenizer = AutoTokenizer.from_pretrained("tuhailong/simcse_model")
>>> sentences_str_list = ["今天天气不错的","天气不错的"]
>>> inputs = tokenizer(sentences_str_list,return_tensors="pt", padding='max_length', truncation=True, max_length=32)
>>> outputs = model(**inputs)
``` |