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e34c552282
* add llama2 test * fix * test qwen chat-7b * test w4 * add baichuan2 * update * update * update configs and docs * update
92 lines
2.6 KiB
Python
92 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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internlm_7b = 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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# # config for internlm-7b-w4 model
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internlm_7b_w4 = 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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# # config for internlm-7b-w4kv8 model
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internlm_7b_w4kv8 = 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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# config for internlm-20b model
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internlm_20b = 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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# config for internlm-20b-w4 model
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internlm_20b_w4 = 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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# config for internlm-20b-w4kv8 model
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internlm_20b_w4kv8 = 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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models = [internlm_20b]
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