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gpt2-ml

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GPT2 for Multiple Languages, including pretrained models. GPT2 多语言支持, 15亿参数中文预训练模型

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최종 버전 다운로드 (.zip)

- - bug_report.md
  - discussion.md
  - feature_request.md
- demo.png
- logo.png
- logo.svg
- loss.png
- stale.yml
- - gdown.pl
  - LICENSE.txt
  - README.md
- base.json
- large.json
- mega.json
- prepare_data.py
- prepare_data.sh
- README.md
- gpu-jupyter.Dockerfile
- demo.py
- down_gdrive_file.py
- __init__.py
- bert-base-chinese-vocab.txt
- bert-large-cased-whole-word-masking-vocab.txt
- clue-vocab.txt
- tokenization.py
- __init__.py
- dataloader.py
- modeling.py
- optimization_adafactor.py
- train_tpu.py
- train_tpu_adafactor.sh
- utils.py
.gitignore
LICENSE
pretrained_model_demo.ipynb
README.md
README_CN.md
requirements-gpu.txt
requirements-tpu.txt

// repository documentation

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<img src="./.github/logo.svg" width="480">

# **GPT2** for Multiple Languages

[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/imcaspar/gpt2-ml/blob/master/pretrained_model_demo.ipynb)
[![GitHub](https://img.shields.io/github/license/imcaspar/gpt2-ml)](https://github.com/imcaspar/gpt2-ml)
[![GitHub All Releases](https://img.shields.io/github/downloads/imcaspar/gpt2-ml/total)](https://github.com/imcaspar/gpt2-ml/releases)
[![contributions welcome](https://img.shields.io/badge/contributions-welcome-brightgreen.svg?style=flat)](https://github.com/imcaspar/gpt2-ml/issues)
[![GitHub stars](https://img.shields.io/github/stars/imcaspar/gpt2-ml?style=social)](https://github.com/imcaspar/gpt2-ml)

[**中文说明**](./README_CN.md) | [**English**](./README.md)

- [x] Simplifed GPT2 train scripts（based on Grover, supporting TPUs）
- [x] Ported bert tokenizer, multilingual corpus compatible
- [x] 1.5B GPT2 pretrained Chinese model ( ~15G corpus, 10w steps )
- [x] Batteries-included Colab demo [#](https://github.com/imcaspar/gpt2-ml#google-colab)
- [x] 1.5B GPT2 pretrained Chinese model ( ~30G corpus, 22w steps )

## Pretrained Model
| Size | Language | Corpus | Vocab | Link1 | Link2 | SHA256 |
| ---- | -------- | ------ | ----- | ----- | ----- | ------ |
| 1.5B Params | Chinese  | ~30G   | CLUE ( 8021 tokens )  | [**Google Drive**](https://drive.google.com/file/d/1mT_qCQg4AWnAXTwKfsyyRWCRpgPrBJS3) | [**Baidu Pan (ffz6)**](https://pan.baidu.com/s/1yiuTHXUr2DpyBqmFYLJH6A) | e698cc97a7f5f706f84f58bb469d614e<br/>51d3c0ce5f9ab9bf77e01e3fcb41d482 |
| 1.5B Params | Chinese  | ~15G   | Bert ( 21128 tokens ) | [**Google Drive**](https://drive.google.com/file/d/1IzWpQ6I2IgfV7CldZvFJnZ9byNDZdO4n) | [**Baidu Pan (q9vr)**](https://pan.baidu.com/s/1TA_3e-u2bXg_hcx_NwVbGw) | 4a6e5124df8db7ac2bdd902e6191b807<br/>a6983a7f5d09fb10ce011f9a073b183e |

Corpus from [THUCNews](http://thuctc.thunlp.org/#%E4%B8%AD%E6%96%87%E6%96%87%E6%9C%AC%E5%88%86%E7%B1%BB%E6%95%B0%E6%8D%AE%E9%9B%86THUCNews) and [nlp_chinese_corpus](https://github.com/brightmart/nlp_chinese_corpus)

Using [Cloud TPU Pod v3-256](https://cloud.google.com/tpu/docs/types-zones#types) to train 22w steps

![loss](https://raw.githubusercontent.com/imcaspar/gpt2-ml/master/.github/loss.png)

## Google Colab
With just 2 clicks (not including Colab auth process), the 1.5B pretrained Chinese model demo is ready to go:

[**[Colab Notebook]**](https://colab.research.google.com/github/imcaspar/gpt2-ml/blob/master/pretrained_model_demo.ipynb)

<img src="./.github/demo.png" width="640">

## Train

## Disclaimer
The contents in this repository are for academic research purpose, and we do not provide any conclusive remarks.

## Citation

```
@misc{GPT2-ML,
  author = {Zhibo Zhang},
  title = {GPT2-ML: GPT-2 for Multiple Languages},
  year = {2019},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/imcaspar/gpt2-ml}},
}
```

## Reference
https://github.com/google-research/bert

https://github.com/rowanz/grover

Research supported with Cloud TPUs from Google's TensorFlow Research Cloud (TFRC)

## Press
[[机器之心] 只需单击三次，让中文GPT-2为你生成定制故事](https://mp.weixin.qq.com/s/FpoSNNKZSQOE2diPvJDHog)

[[科学空间] 现在可以用Keras玩中文GPT2了](https://kexue.fm/archives/7292)