Update README.md

README.md

@@ -9,17 +9,15 @@ widget:
 
 ## Model description
 
-This model is used to generate Chinese couplets and is pre-trained by [UER-py](https://www.aclweb.org/anthology/D19-3041.pdf).
+The model is used to generate Chinese couplets. You can download the model either from the [GPT2-Chinese Github page](https://github.com/Morizeyao/GPT2-Chinese), or via HuggingFace from the link [gpt2-chinese-couplet][couplet].
 
-You can download this model via HuggingFace from the link :[gpt2-chinese-couplet][couplet]
+Since the parameter skip_special_tokens is used in the pipelines.py, special tokens such as [SEP], [UNK] will be deleted, and the output results may not be neat.
 
 ## How to use
 
-Because the parameter ***skip_special_tokens*** is used in the ***pipelines.py*** , special tokens such as [SEP], [UNK] will be deleted, and the output results may not be neat.
+You can use the model directly with a pipeline for text generation:
 
-You can use this model directly with a pipeline for text generation:
-
-When the parameter ***skip_special_tokens***  is True:
+When the parameter skip_special_tokens is True:
 
 ```python
 >>> from transformers import BertTokenizer, GPT2LMHeadModel, TextGenerationPipeline
@@ -31,7 +29,7 @@ When the parameter ***skip_special_tokens***  is True:
 	[{'generated_text': '[CLS]丹 枫 江 冷 人 初 去 - 黄 叶 声 从 天 外 来 阅 旗'}]
 ```
 
-When the parameter ***skip_special_tokens***  is Flase:
+When the parameter skip_special_tokens is False:
 
 ```python
 >>> from transformers import BertTokenizer, GPT2LMHeadModel, TextGenerationPipeline
@@ -45,7 +43,7 @@ When the parameter ***skip_special_tokens***  is Flase:
 
 ## Training data
 
-Contains about 700,000 chinese couplets.
+Contains 700,000 Chinese couplets collected by [couplet-clean-dataset](https://github.com/v-zich/couplet-clean-dataset).
 
 ## Training procedure