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* Add NeedleInAHaystack Test * Apply pre-commit formatting * Update configs/eval_hf_internlm_chat_20b_cdme.py Co-authored-by: Songyang Zhang <tonysy@users.noreply.github.com> * add needle in haystack test * update needle in haystack test * update plot function in tools_needleinahaystack.py * optimizing needleinahaystack dataset generation strategy * modify minor formatting issues * add English version support * change NeedleInAHaystackDataset to dynamic loading * change NeedleInAHaystackDataset to dynamic loading * fix needleinahaystack test eval bug * fix needleinahaystack config bug * Added support for multi-needle testing in needle-in-a-haystack test * Optimize the code for plotting in the needle-in-a-haystack test. * Correct the typo in the dataset parameters. * update needleinahaystack test docs --------- Co-authored-by: Songyang Zhang <tonysy@users.noreply.github.com>
29 lines
769 B
Python
29 lines
769 B
Python
from opencompass.models.turbomind import TurboMindModel
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from mmengine.config import read_base
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with read_base():
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from .datasets.cdme.cdme200k import cdme_datasets
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datasets = [*cdme_datasets]
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internlm_meta_template = dict(round=[
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dict(role='HUMAN', begin='<|User|>:', end='\n'),
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dict(role='BOT', begin='<|Bot|>:', end='<eoa>\n', generate=True),
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],
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eos_token_id=103028)
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models = [
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# config for internlm-chat-20b
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dict(
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type=TurboMindModel,
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abbr='internlm-chat-20b-turbomind',
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path='./turbomind',
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max_out_len=100,
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max_seq_len=201000,
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batch_size=8,
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concurrency=8,
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meta_template=internlm_meta_template,
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run_cfg=dict(num_gpus=1, num_procs=1),
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)
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]
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