# nezha-cn-base

**Repository Path**: modelee/nezha-cn-base

## Basic Information

- **Project Name**: nezha-cn-base
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2023-05-23
- **Last Updated**: 2024-04-02

## Categories & Tags

**Categories**: llm

**Tags**: None

## README

---
license: afl-3.0
---
**Please use 'Bert' related tokenizer classes and 'Nezha' related model classes**

[NEZHA: Neural Contextualized Representation for Chinese Language Understanding](https://arxiv.org/abs/1909.00204)
Junqiu Wei, Xiaozhe Ren, Xiaoguang Li, Wenyong Huang, Yi Liao, Yasheng Wang, Jiashu Lin, Xin Jiang, Xiao Chen and Qun Liu.

The original checkpoints can be found [here](https://github.com/huawei-noah/Pretrained-Language-Model/tree/master/NEZHA-PyTorch)

## Example Usage

```
from transformers import BertTokenizer, NezhaModel
tokenizer = BertTokenizer.from_pretrained('sijunhe/nezha-cn-base')
model = NezhaModel.from_pretrained("sijunhe/nezha-cn-base")
text = "我爱北京天安门"
encoded_input = tokenizer(text, return_tensors='pt')
output = model(**encoded_input)
```