Update README.md

README.md

@@ -1,3 +1,110 @@
 ---
-license: apache-2.0
+language: 
+- zh
+tags:
+- songnet
+- pytorch
+- zh
+- Text2Text-Generation
+license: "apache-2.0"
+widget:
+- text: "丹枫江冷人初去"
+
 ---
+
+# SongNet for Chinese Couplet(songnet-base-chinese-couplet) Model
+SongNet中文对联生成模型
+
+`songnet-base-chinese-couplet` evaluate couplet test data：
+
+The overall performance of T5 on couplet **test**:
+
+|input_text|target_text|pred|
+|:--- |:--- |:-- |
+|春回大地，对对黄莺鸣暖树|日照神州，群群紫燕衔新泥|福至人间,家家紫燕舞和风|
+
+在Couplet测试集上生成结果满足字数相同、词性对齐、词面对齐、形似要求，针对性的SongNet网络结构，在语义对仗工整和平仄合律上的效果明显优于T5和GPT2等模型。
+
+SongNet的网络结构：
+
+![arch](songnet-network.png)
+
+## Usage
+
+本项目开源在文本生成项目：[textgen](https://github.com/shibing624/textgen)，可支持SongNet模型，通过如下命令调用：
+
+Install package:
+```shell
+pip install -U textgen
+```
+
+```python
+import sys
+
+sys.path.append('..')
+from textgen.language_modeling import SongNetModel
+
+
+model = SongNetModel(model_type='songnet', model_name='songnet-base-chinese-couplet')
+sentences = [
+    "严蕊<s1>如梦令<s2>道是梨花不是。</s>道是杏花不是。</s>白白与红红，别是东风情味。</s>曾记。</s>曾记。</s>人在武陵微醉。",
+    "<s1><s2>一句相思吟岁月</s>千杯美酒醉风情",
+    "<s1><s2>几树梅花数竿竹</s>一潭秋水半屏山"
+    "<s1><s2>未舍东江开口咏</s>且施妙手点睛来",
+    "<s1><s2>一去二三里</s>烟村四五家",
+]
+print("inputs:", sentences)
+print("outputs:", model.generate(sentences))
+sentences = [
+    "<s1><s2>一句____月</s>千杯美酒__情",
+    "<s1><s2>一去二三里</s>烟村__家</s>亭台__座</s>八__枝花",
+]
+print("inputs:", sentences)
+print("outputs:", model.fill_mask(sentences))
+
+```
+
+
+模型文件组成：
+```
+t5-chinese-couplet
+    ├── pytorch_model.bin
+    └── vocab.txt
+```
+
+
+### 训练数据集
+#### 中文对联数据集
+
+- 数据：[对联github](https://github.com/wb14123/couplet-dataset)、[清洗过的对联github](https://github.com/v-zich/couplet-clean-dataset)
+- 相关内容
+  - [Huggingface](https://huggingface.co/)
+  - [SongNet paper](https://aclanthology.org/2020.acl-main.68/)
+  - [textgen](https://github.com/shibing624/textgen)
+  
+  
+数据格式：
+
+```text
+head -n 1 couplet_files/couplet/train/in.txt
+晚 风 摇 树 树 还 挺 
+
+head -n 1 couplet_files/couplet/train/out.txt
+晨 露 润 花 花 更 红 
+```
+
+
+如果需要训练SongNet模型，请参考[https://github.com/shibing624/textgen/blob/main/examples/language_generation/training_zh_songnet_demo.py](https://github.com/shibing624/textgen/blob/main/examples/language_generation/training_zh_songnet_demo.py)
+
+
+## Citation
+
+```latex
+@software{textgen,
+  author = {Xu Ming},
+  title = {textgen: Implementation of Text Generation models},
+  year = {2022},
+  url = {https://github.com/shibing624/textgen},
+}
+```
+