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add vllm model configs (#938)
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configs/models/others/vllm_orionstar_14b_longchat.py
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configs/models/others/vllm_orionstar_14b_longchat.py
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from opencompass.models import VLLM
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_meta_template = dict(
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begin='<s>',
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round=[
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dict(role="HUMAN", begin='Human: ', end='\n'),
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dict(role="BOT", begin="Assistant: ", end='</s>', generate=True),
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],
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eos_token_id=2
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)
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models = [
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dict(
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abbr='orionstar-14b-longchat-vllm',
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type=VLLM,
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path='OrionStarAI/Orion-14B-LongChat',
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model_kwargs=dict(tensor_parallel_size=4),
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generation_kwargs=dict(temperature=0),
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meta_template=_meta_template,
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max_out_len=100,
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max_seq_len=4096,
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batch_size=32,
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run_cfg=dict(num_gpus=4, num_procs=1),
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end_str='<|endoftext|>',
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)
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]
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configs/models/qwen/vllm_qwen1_5_14b_chat.py
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configs/models/qwen/vllm_qwen1_5_14b_chat.py
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from opencompass.models import VLLM
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_meta_template = dict(
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round=[
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dict(role="HUMAN", begin='<|im_start|>user\n', end='<|im_end|>\n'),
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dict(role="BOT", begin="<|im_start|>assistant\n", end='<|im_end|>\n',
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generate=True),
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],
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eos_token_id=151645,
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)
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models = [
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dict(
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type=VLLM,
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abbr='qwen1.5-14b-chat-vllm',
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path="Qwen/Qwen1.5-14B-Chat",
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model_kwargs=dict(tensor_parallel_size=2),
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meta_template=_meta_template,
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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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generation_kwargs=dict(temperature=0),
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end_str='<|im_end|>',
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run_cfg=dict(num_gpus=2, num_procs=1),
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)
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]
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