* feat(run_eval): add checkpoint resume functionality and update example documentation;
- update new bootcamp benchmark dataset
* refactor(data_pipeline): optimize data generation pipeline; add multiple preset configurations for data generation
* docs: update bootcamp list and add new scripts
- Update Fulllist_InternBootcamp.md with new bootcamps and categories
- Add new scripts to .gitignore:
- examples/pipelines/filter_autogen_configs.py
- examples/pipelines/quickgen_data_configs_from_eval_meta.py
- Update dependencies in setup.py:
- Add scipy and scikit-learn
* refactor(internbootcamp): update bootcamp modules and improve error handling
- Update import statements in __init__.py files
- Add timestamp to target directory name in verl_data_preprocess.py
- Improve error handling and scoring logic in bootcamp_judger.py
- Remove unnecessary comments and update puzzle descriptions in multiple files
- Update quick start guide for data generation, model training, and evaluation
- Add detailed instructions for creating custom Bootcamp tasks
- Update examples in both English and Chinese documentation
- Add quick start guide for InternBootcamp in both English and Chinese
- Update README and README_zh to include new quick start links
- Create detailed documentation for using Xtuner with Bootcamp data
