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https://github.com/InternLM/InternBootcamp.git
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a8249acc18
* 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
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953 B
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41 lines
No EOL
953 B
JSON
[
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{
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"min_n": 8,
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"max_n": 30,
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"attribute_descriptions": [
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"top scorer",
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"perfect health",
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"satisfied customer",
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"damaged goods",
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"active lifestyle",
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"excessive noise",
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"full recovery"
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]
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},
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{
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"min_n": 3,
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"max_n": 20,
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"attribute_descriptions": [
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"excellent performance",
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"no diseases",
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"content with product",
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"faulty goods",
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"consistent work",
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"high pollution",
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"successful surgery"
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]
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},
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{
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"min_n": 5,
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"max_n": 50,
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"attribute_descriptions": [
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"math score above 90",
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"healthy",
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"satisfied with facilities",
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"defective",
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"daily exercise",
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"speeding behavior",
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"positive response"
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]
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}
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] |