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