---
language: zh
tags:
- summarization
inference: False
---

Randeng_egasus_238M_summary model (Chinese)，codes has merged into [Fengshenbang-LM](https://github.com/IDEA-CCNL/Fengshenbang-LM)

The 523M million parameter randeng_pegasus_large model, training with sampled gap sentence ratios on 180G Chinese data, and stochastically sample important sentences. The pretraining task just same as the paper [PEGASUS: Pre-training with Extracted Gap-sentences for
Abstractive Summarization](https://arxiv.org/pdf/1912.08777.pdf) mentioned.

Different from the English version of pegasus, considering that the Chinese sentence piece is unstable, we use jieba and Bertokenizer as the tokenizer in chinese pegasus model.

We also pretained a large model , available with [Randeng_Pegasus_523M_Summary](https://huggingface.co/IDEA-CCNL/Randeng_Pegasus_523M_Summary)

Task: Summarization

## Usage
```python
from transformers import PegasusForConditionalGeneration
# Need to download tokenizers_pegasus.py and other Python script from Fengshenbang-LM github repo in advance
from tokenizers_pegasus import PegasusTokenizer

model = PegasusForConditionalGeneration.from_pretrained("IDEA-CCNL/randeng_pegasus_238M_summary")
tokenizer = PegasusTokenizer.from_pretrained("path/to/vocab.txt")

text = "在北京冬奥会自由式滑雪女子坡面障碍技巧决赛中，中国选手谷爱凌夺得银牌。祝贺谷爱凌！今天上午，自由式滑雪女子坡面障碍技巧决赛举行。决赛分三轮进行，取选手最佳成绩排名决出奖牌。第一跳，中国选手谷爱凌获得69.90分。在12位选手中排名第三。完成动作后，谷爱凌又扮了个鬼脸，甚是可爱。第二轮中，谷爱凌在道具区第三个障碍处失误，落地时摔倒。获得16.98分。网友：摔倒了也没关系，继续加油！在第二跳失误摔倒的情况下，谷爱凌顶住压力，第三跳稳稳发挥，流畅落地！获得86.23分！此轮比赛，共12位选手参赛，谷爱凌第10位出场。网友：看比赛时我比谷爱凌紧张，加油！"
inputs = tokenizer(text, max_length=1024, return_tensors="pt")

# Generate Summary
summary_ids = model.generate(inputs["input_ids"])
tokenizer.batch_decode(summary_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
```

## Citation
If you find the resource is useful, please cite the following website in your paper.
```
@misc{Fengshenbang-LM,
  title={Fengshenbang-LM},
  author={IDEA-CCNL},
  year={2022},
  howpublished={\url{https://github.com/IDEA-CCNL/Fengshenbang-LM}},
}
```