---
title: chinese-electra-small-generator
canonical_url: "https://www.modelscope.cn/models/dienstag/chinese-electra-small-generator"
md_url: "https://www.modelscope.cn/models/dienstag/chinese-electra-small-generator.md"
repository: dienstag/chinese-electra-small-generator
last_updated: 2023-03-07
license: apache-2.0
pipeline_tag: fill-mask
tasks:
  - fill-mask
model_type:
  - electra
library_name:
  - tensorflow
  - pytorch
frameworks:
  - pytorch
language:
  - zh
downloads: 112
stars: 0
---

# chinese-electra-small-generator

> chinese-electra-small-generator - dienstag 在 ModelScope 开源的模型。Please use ElectraForPreTraining for discriminator and ElectraForMaskedLM for generator if you are re-training these models.

dienstag/chinese-electra-small-generator 是 ModelScope 魔搭社区上的fill-mask模型，采用 apache-2.0 许可。

- **Repository**: dienstag/chinese-electra-small-generator
- **License**: apache-2.0
- **Tasks**: fill-mask
- **Downloads**: 112
- **Stars**: 0
- **Last updated**: 2023-03-07

Source: https://www.modelscope.cn/models/dienstag/chinese-electra-small-generator

---

**Please use `ElectraForPreTraining` for `discriminator` and `ElectraForMaskedLM` for `generator` if you are re-training these models.**

## Chinese ELECTRA
Google and Stanford University released a new pre-trained model called ELECTRA, which has a much compact model size and relatively competitive performance compared to BERT and its variants.
For further accelerating the research of the Chinese pre-trained model, the Joint Laboratory of HIT and iFLYTEK Research (HFL) has released the Chinese ELECTRA models based on the official code of ELECTRA.
ELECTRA-small could reach similar or even higher scores on several NLP tasks with only 1/10 parameters compared to BERT and its variants.

This project is based on the official code of ELECTRA: [https://github.com/google-research/electra](https://github.com/google-research/electra)

You may also interested in,
- Chinese BERT series: https://github.com/ymcui/Chinese-BERT-wwm
- Chinese ELECTRA: https://github.com/ymcui/Chinese-ELECTRA
- Chinese XLNet: https://github.com/ymcui/Chinese-XLNet
- Knowledge Distillation Toolkit - TextBrewer: https://github.com/airaria/TextBrewer

More resources by HFL: https://github.com/ymcui/HFL-Anthology

## 示例代码
```python
from modelscope.pipelines import pipeline
from modelscope.utils.constant import Tasks

pipeline_ins = pipeline(
		'fill-mask',
		model='dienstag/chinese-electra-small-generator',
        model_revision='v1.0.0'
)

print(pipeline_ins('生活的真谛是[MASK]。'))
```


## Citation
If you find our resource or paper is useful, please consider including the following citation in your paper.
- https://arxiv.org/abs/2004.13922
```
@inproceedings{cui-etal-2020-revisiting,
    title = "Revisiting Pre-Trained Models for {C}hinese Natural Language Processing",
    author = "Cui, Yiming  and
      Che, Wanxiang  and
      Liu, Ting  and
      Qin, Bing  and
      Wang, Shijin  and
      Hu, Guoping",
    booktitle = "Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: Findings",
    month = nov,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/2020.findings-emnlp.58",
    pages = "657--668",
}
```