Data

train data is similarity sentence data from E-commerce dialogue, about 50w sentence pairs.

Model

model created by sentence-tansformers,model struct is cross-encoder,pretrained model is hfl/chinese-roberta-wwm-ext.

Usage

>>> 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])

Code

train code from https://github.com/TTurn/cross-encoder

Downloads last month
17
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.