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eb56fd6d16
* integrate turbomind python api * update * update user guide * update * fix according to reviewer's comments * fix error * fix linting * update user guide * remove debug log --------- Co-authored-by: Songyang Zhang <tonysy@users.noreply.github.com>
102 lines
2.6 KiB
Python
102 lines
2.6 KiB
Python
from mmengine.config import read_base
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from opencompass.models.turbomind import TurboMindModel
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with read_base():
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# choose a list of datasets
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from .datasets.mmlu.mmlu_gen_a484b3 import mmlu_datasets
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from .datasets.ceval.ceval_gen_5f30c7 import ceval_datasets
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from .datasets.SuperGLUE_WiC.SuperGLUE_WiC_gen_d06864 import WiC_datasets
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from .datasets.triviaqa.triviaqa_gen_2121ce import triviaqa_datasets
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from .datasets.gsm8k.gsm8k_gen_1d7fe4 import gsm8k_datasets
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from .datasets.humaneval.humaneval_gen_8e312c import humaneval_datasets
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# and output the results in a choosen format
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from .summarizers.medium import summarizer
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datasets = sum((v for k, v in locals().items() if k.endswith('_datasets')), [])
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# # config for internlm-7b model
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# models = [
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# dict(
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# type=TurboMindModel,
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# abbr='internlm-7b-turbomind',
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# path="./turbomind",
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# max_out_len=100,
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# max_seq_len=2048,
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# batch_size=32,
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# concurrency=32,
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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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# # config for internlm-7b-w4 model
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# models = [
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# dict(
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# type=TurboMindModel,
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# abbr='internlm-7b-w4-turbomind',
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# path="./turbomind",
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# max_out_len=100,
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# max_seq_len=2048,
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# batch_size=32,
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# concurrency=32,
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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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# # config for internlm-7b-w4kv8 model
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# models = [
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# dict(
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# type=TurboMindModel,
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# abbr='internlm-7b-w4kv8-turbomind',
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# path="./turbomind",
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# max_out_len=100,
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# max_seq_len=2048,
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# batch_size=32,
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# concurrency=32,
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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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# config for internlm-20b model
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models = [
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dict(
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type=TurboMindModel,
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abbr='internlm-20b-turbomind',
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path="./turbomind",
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max_out_len=100,
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max_seq_len=2048,
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batch_size=8,
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concurrency=8,
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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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# config for internlm-20b-w4 model
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# models = [
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# dict(
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# type=TurboMindModel,
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# abbr='internlm-20b-w4-turbomind',
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# path="./turbomind",
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# max_out_len=100,
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# max_seq_len=2048,
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# batch_size=16,
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# concurrency=16,
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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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# config for internlm-20b-w4kv8 model
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# models = [
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# dict(
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# type=TurboMindModel,
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# abbr='internlm-20b-w4kv8-turbomind',
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# path="./turbomind",
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# max_out_len=100,
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# max_seq_len=2048,
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# batch_size=16,
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# concurrency=16,
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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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