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

## Model
model created by [sentence-tansformers](https://www.sbert.net/index.html)，model struct is cross-encoder，pretrained model is hfl/chinese-roberta-wwm-ext-large.

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

#### Usage
```python
>>> 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])
```
{"language": "zh", "tags": ["cross-encoder"], "datasets": ["dialogue"]}
transformers pytorch bert text-classification cross-encoder zh dataset:dialogue autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #cross-encoder #zh #dataset-dialogue #autotrain_compatible #endpoints_compatible #region-us 


# 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-large.

### Code
train code from URL

#### Usage

# 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-large. ### Code
train code from URL #### Usage
TAGS
#transformers #pytorch #bert #text-classification #cross-encoder #zh #dataset-dialogue #autotrain_compatible #endpoints_compatible #region-us 
 # 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-large. ### Code
train code from URL #### Usage
passage: TAGS
#transformers #pytorch #bert #text-classification #cross-encoder #zh #dataset-dialogue #autotrain_compatible #endpoints_compatible #region-us 
# 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-large.### Code
train code from URL#### Usage