Create README.md

README.md

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+---
+language: zh
+tags:
+- summarization
+inference: False
+---
+
+IDEA-CCNL/Randeng_Pegasus_238M_Summary_Chinese model (Chinese) has 238M million parameter, pretrained on 180G Chinese data with GSG task which is stochastically sample important sentences with sampled gap sentence ratios by 25%. The pretraining task just as same as the paper PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization 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.
+
+After pre-training, We use 8 summary datasets which we collect on the internet to do the supervised training. The 8 datasets include education_data, new2016zh_data, nlpcc, shence_data, sohu_data, thucnews_data and weibo_data, four million training samples in all.
+
+
+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,
+# or you can download tokenizers_pegasus.py and data_utils.py in https://huggingface.co/IDEA-CCNL/Randeng_Pegasus_523M/tree/main
+# Strongly recommend you git clone the Fengshenbang-LM repo:
+# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
+# 2. cd Fengshenbang-LM/fengshen/examples/pegasus/
+# and then you will see the tokenizers_pegasus.py and data_utils.py which are needed by pegasus model
+from tokenizers_pegasus import PegasusTokenizer
+
+model = PegasusForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Pegasus-238M-Summary-Chinese")
+tokenizer = PegasusTokenizer.from_pretrained("IDEA-CCNL/Randeng-Pegasus-238M-Summary-Chinese")
+
+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]
+
+# model Output: 滑雪女子坡面障碍技巧决赛：中国选手谷爱凌摘银
+```
+
+## 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}},
+}
+```