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7505b3cadf
* add TheoremQA with 5-shot * add huggingface_above_v4_33 classes * use num_worker partitioner in cli * update theoremqa * update TheoremQA * add TheoremQA * rename theoremqa -> TheoremQA * update TheoremQA output path * rewrite many model configs * update huggingface * further update * refine configs * update configs * update configs * add configs/eval_llama3_instruct.py * add summarizer multi faceted * update bbh datasets * update configs/models/hf_llama/lmdeploy_llama3_8b_instruct.py * rename class * update readme * update hf above v4.33
26 lines
664 B
Python
26 lines
664 B
Python
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', 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=VLLM,
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abbr='qwen1.5-72b-chat-vllm',
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path="Qwen/Qwen1.5-72B-Chat",
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model_kwargs=dict(tensor_parallel_size=4),
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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=4, num_procs=1),
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)
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]
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