metadata
language: zh
tags:
- simcse
datasets:
- dialogue
Data
train data is similar data from E-commerce dialogue
Model
model created by sentence-tansformers,model struct is cross-encoder
Usage
>>> 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)