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39 lines
1.1 KiB
Python
39 lines
1.1 KiB
Python
from mmengine.config import read_base
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from opencompass.models import OpenAI
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from opencompass.partitioners import NaivePartitioner
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from opencompass.runners import LocalRunner
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from opencompass.tasks import OpenICLInferTask
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with read_base():
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# choose a list of datasets
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from opencompass.configs.datasets.collections.chat_medium import datasets
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# and output the results in a choosen format
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from opencompass.configs.summarizers.medium import summarizer
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api_meta_template = dict(round=[
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dict(role='HUMAN', api_role='HUMAN'),
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dict(role='BOT', api_role='BOT', generate=True),
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], )
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models = [
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dict(
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abbr='GPT-3.5-turbo-0613',
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type=OpenAI,
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path='gpt-3.5-turbo-0613',
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key=
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'ENV', # The key will be obtained from $OPENAI_API_KEY, but you can write down your key here as well
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meta_template=api_meta_template,
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query_per_second=1,
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max_out_len=2048,
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max_seq_len=4096,
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batch_size=8),
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]
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infer = dict(
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partitioner=dict(type=NaivePartitioner),
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runner=dict(type=LocalRunner,
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max_num_workers=8,
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task=dict(type=OpenICLInferTask)),
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)
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