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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
1.2 KiB
Python
39 lines
1.2 KiB
Python
from opencompass.partitioners import (
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NaivePartitioner,
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NumWorkerPartitioner,
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)
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from mmengine.config import read_base
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from opencompass.runners import LocalRunner
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from opencompass.tasks import OpenICLInferTask, OpenICLEvalTask
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with read_base():
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from ..configs.models.hf_internlm.lmdeploy_internlm2_5_7b_chat_1m import (
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models as internlm2_5_7b_chat_1m,
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)
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from .datasets.ruler.ruler_combined_gen import ruler_combined_datasets
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from ..configs.summarizers.groups.ruler import ruler_summary_groups
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datasets = sum((v for k, v in locals().items() if k.endswith('_datasets')), [])
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models = internlm2_5_7b_chat_1m
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work_dir = './outputs/ruler'
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infer = dict(
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partitioner=dict(type=NumWorkerPartitioner, num_worker=2),
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runner=dict(
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type=LocalRunner, max_num_workers=16, task=dict(type=OpenICLInferTask), retry=5
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),
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)
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eval = dict(
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partitioner=dict(type=NaivePartitioner),
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runner=dict(type=LocalRunner, max_num_workers=32, task=dict(type=OpenICLEvalTask)),
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)
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summarizer = dict(
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dataset_abbrs=['ruler_4k', 'ruler_8k', 'ruler_16k', 'ruler_32k'],
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summary_groups=sum(
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[v for k, v in locals().items() if k.endswith('_summary_groups')], []
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),
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)
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