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
- 8
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.