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a4b54048ae
* [Feature] Add Ruler datasets * pre-commit fixed * Add model specific tokenizer to dataset * pre-commit modified * remove unused import * fix linting * add trust_remote to tokenizer load * lint fix * comments resolved * fix lint * Add readme * Fix lint * ruler refactorize * fix lint * lint fix * updated * lint fix * fix wonderwords import issue * prompt modified * update * readme updated * update * ruler dataset added * Update --------- Co-authored-by: tonysy <sy.zhangbuaa@gmail.com>
39 lines
1.4 KiB
Python
39 lines
1.4 KiB
Python
from opencompass.openicl.icl_prompt_template import PromptTemplate
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from opencompass.openicl.icl_retriever import ZeroRetriever
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from opencompass.openicl.icl_inferencer import GenInferencer
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from opencompass.datasets.ruler.ruler_qa import RulerQaDataset
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from opencompass.datasets.ruler.ruler_qa import RulerQaEvaluator
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qa_configurations = [
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{'dataset': 'squad', 'path': './data/ruler/dev-v2.0.json'},
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{'dataset': 'hotpotqa', 'path': './data/ruler/hotpotqa.json'},
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]
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qa_datasets = []
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for index, config in enumerate(qa_configurations):
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dataset_dict = {
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'abbr': f'ruler_qa_{config["dataset"]}',
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'dataset': config['dataset'],
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'path': config['path'],
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'type': RulerQaDataset,
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'tokens_to_generate': 50,
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'reader_cfg': dict(input_columns=['prompt'], output_column='answer'),
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'infer_cfg': dict(
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prompt_template=dict(
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type=PromptTemplate,
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template=dict(
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round=[
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dict(role='HUMAN', prompt='{prompt}'),
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dict(role='BOT', prompt='{answer}\n'),
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]
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),
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),
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retriever=dict(type=ZeroRetriever),
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inferencer=dict(type=GenInferencer),
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),
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'eval_cfg': dict(
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evaluator=dict(type=RulerQaEvaluator),
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),
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}
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qa_datasets.append(dataset_dict)
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