主要做了如下修改：
1. 加入了同义词词典
2. 对SQL进行后处理，如果包含排序，则将空列转化成Primary列
        Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10670121

修复header_ids和header_names命名反了的问题
        Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10516557

Features:
1. Refactor the directory structure of nlp models. All model files are placed into either the model folder or the task_model folder
2. Refactor all the comments to google style
3. Add detail comments to important tasks and nlp models, to list the description of the model, and its preprocessor&trainer
4. Model Exporting now supports a direct all to TorchModelExporter(no need to derive from it)
5. Refactor model save_pretrained method to support direct running(independent from trainer)
6. Remove the judgement of Model in the pipeline base class, to support outer register models running in our pipelines
7. Nlp trainer now has a NLPTrainingArguments class , user can pass arguments into the dataclass, and use it as a normal cfg_modify_fn, to simplify the operation of modify cfg.
8. Merge the BACKBONES and the MODELS, so user can get a backbone with the Model.from_pretrained call
9. Model.from_pretrained now support a task argument, so user can use a backbone and load it with a specific task class.
10. Support Preprocessor.from_pretrained method
11. Add standard return classes to important nlp tasks, so some of the pipelines and the models are independent now, the return values of the models will always be tensors, and the pipelines will take care of the conversion to numpy and the following stuffs.
12. Split the file of the nlp preprocessors, to make the dir structure more clear.

Bugs Fixing:
1. Fix a bug that lr_scheduler can be called earlier than the optimizer's step
2. Fix a bug that the direct call of Pipelines (not from pipeline(xxx)) throws error
3. Fix a bug that the trainer will not call the correct TaskDataset class
4. Fix a bug that the internal loading of dataset will throws error in the trainer class
        Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10490585

1. 修复multi thread引起的问题
2. 增加multi thread的unittest
        Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10502008

1. 合并star和star3框架
2. 修改star和star3的model type
        Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10492793

1. 增加传入table_id
2. 将result和table的结构统一
3. 默认开启is_use_sqlite
        Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10492027

修改output的结构，直接返回可转化成json format的结构
        Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10415403

相比于master上的tableqa，做出了如下修复：
1. 修复了schema linking中的问题。
2. 同时设置了有history sql和没有history sql的两种输入
3. 增加了sqlite执行逻辑，可以返回sql执行结果
        Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10365114

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10142442

commit nlp_convai_text2sql_pretrain_cn inference process to modelscope
        Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10025155