## **For better user experience, refer to the Web official document -> [Language Model](https://www.paddlepaddle.org.cn/hublist)**

### Language Model

- Recommended Model

| Model Name                                                   | Module Introduction                                          |
| ------------------------------------------------------------ | ------------------------------------------------------------ |
| [Word embedding model](https://www.paddlepaddle.org.cn/hubdetail?name=word2vec_skipgram&en_category=SemanticModel) | In the massive Baidu search dataset, the Chinese character pre-training word embedding is obtained through pre-training. It supports Fine-tune. The vocabulary list size of Word2vec's pre-training dataset is 1700249. The word embedding dimension is 128. |
| [Text similarity](https://www.paddlepaddle.org.cn/hubdetail?name=simnet_bow&en_category=SemanticModel) | Based on the two texts entered by a user, the score of the text similarity is calculated. |

| [ERNIE](https://www.paddlepaddle.org.cn/hubdetail?name=ERNIE&en_category=SemanticModel) |Based on Chinese corpus self-developed models such as encyclopedia, information, and forum dialogue data, it can be used for tasks such as text classification, sequence annotation, and reading comprehension.  
