
# liam168/c4-zh-distilbert-base-uncased

## Model description

用 ["女性","体育","文学","校园"]4类数据训练的分类模型。

## Overview

- **Language model**: DistilBERT
- **Model size**: 280M 
- **Language**: Chinese

## Example

```python
>>> from transformers import DistilBertForSequenceClassification , AutoTokenizer, pipeline

>>> model_name = "liam168/c4-zh-distilbert-base-uncased"
>>> class_num = 4
>>> ts_texts = ["女人做得越纯粹，皮肤和身材就越好", "我喜欢篮球"]
>>> model = DistilBertForSequenceClassification.from_pretrained(model_name, num_labels=class_num)
>>> tokenizer = AutoTokenizer.from_pretrained(model_name)
>>> classifier = pipeline('sentiment-analysis', model=model, tokenizer=tokenizer)
>>> classifier(ts_texts[0])
>>> classifier(ts_texts[1])

[{'label': 'Female', 'score': 0.9137857556343079}]
[{'label': 'Sports', 'score': 0.8206522464752197}]

```

{"language": "zh", "license": "apache-2.0", "tags": ["exbert"], "widget": [{"text": "\u5973\u4eba\u505a\u5f97\u8d8a\u7eaf\u7cb9\uff0c\u76ae\u80a4\u548c\u8eab\u6750\u5c31\u8d8a\u597d"}, {"text": "\u6211\u559c\u6b22\u7bee\u7403"}]}
transformers pytorch distilbert text-classification exbert zh license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #distilbert #text-classification #exbert #zh #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 


# liam168/c4-zh-distilbert-base-uncased

## Model description

用 ["女性","体育","文学","校园"]4类数据训练的分类模型。

## Overview

- Language model: DistilBERT
- Model size: 280M 
- Language: Chinese

## Example



# liam168/c4-zh-distilbert-base-uncased ## Model description

用 ["女性","体育","文学","校园"]4类数据训练的分类模型。 ## Overview

- Language model: DistilBERT
- Model size: 280M 
- Language: Chinese ## Example
TAGS
#transformers #pytorch #distilbert #text-classification #exbert #zh #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 # liam168/c4-zh-distilbert-base-uncased ## Model description

用 ["女性","体育","文学","校园"]4类数据训练的分类模型。 ## Overview

- Language model: DistilBERT
- Model size: 280M 
- Language: Chinese ## Example
passage: TAGS
#transformers #pytorch #distilbert #text-classification #exbert #zh #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
# liam168/c4-zh-distilbert-base-uncased## Model description

用 ["女性","体育","文学","校园"]4类数据训练的分类模型。## Overview

- Language model: DistilBERT
- Model size: 280M 
- Language: Chinese## Example