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27 lines
1.0 KiB
Python
27 lines
1.0 KiB
Python
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categories = ['mmlu_lite_AR-XY','mmlu_lite_BN-BD','mmlu_lite_DE-DE','mmlu_lite_ES-LA','mmlu_lite_FR-FR','mmlu_lite_HI-IN','mmlu_lite_ID-ID','mmlu_lite_IT-IT','mmlu_lite_JA-JP','mmlu_lite_KO-KR','mmlu_lite_PT-BR','mmlu_lite_SW-KE','mmlu_lite_YO-NG','mmlu_lite_ZH-CN']
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mmmlu_summary_groups = [
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{'name': 'mmmlu_lite', 'subsets': [f'openai_m{c}' for c in categories]},
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]
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summarizer = dict(
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dataset_abbrs=[
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'openai_mmmlu_lite_AR-XY',
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'openai_mmmlu_lite_BN-BD',
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'openai_mmmlu_lite_DE-DE',
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'openai_mmmlu_lite_ES-LA',
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'openai_mmmlu_lite_FR-FR',
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'openai_mmmlu_lite_HI-IN',
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'openai_mmmlu_lite_ID-ID',
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'openai_mmmlu_lite_IT-IT',
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'openai_mmmlu_lite_JA-JP',
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'openai_mmmlu_lite_KO-KR',
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'openai_mmmlu_lite_PT-BR',
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'openai_mmmlu_lite_SW-KE',
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'openai_mmmlu_lite_YO-NG',
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'openai_mmmlu_lite_ZH-CN',
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'mmmlu_lite'
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],
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summary_groups=sum([v for k, v in locals().items() if k.endswith('_summary_groups')], []),
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)
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