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35 lines
900 B
Python
35 lines
900 B
Python
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from opencompass.models import HuggingFaceCausalLM
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_meta_template = dict(
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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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)
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models = [
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dict(
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type=HuggingFaceCausalLM,
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abbr='internlm-chat-7b-v1.1-hf',
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path="internlm/internlm-chat-7b-v1_1",
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tokenizer_path='internlm/internlm-chat-7b-v1_1',
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model_kwargs=dict(
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trust_remote_code=True,
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device_map='auto',
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),
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tokenizer_kwargs=dict(
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padding_side='left',
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truncation_side='left',
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use_fast=False,
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trust_remote_code=True,
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),
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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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meta_template=_meta_template,
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run_cfg=dict(num_gpus=1, num_procs=1),
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end_str='<eoa>',
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)
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]
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