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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
37 lines
942 B
Python
37 lines
942 B
Python
from opencompass.models.turbomind import TurboMindModel
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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=TurboMindModel,
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abbr="internlm2-chat-7b-turbomind",
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path="internlm/internlm2-chat-7b",
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meta_template=_meta_template,
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engine_config=dict(
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session_len=32768,
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max_batch_size=32,
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model_name="internlm2-chat-7b",
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tp=1,
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stop_words=[2, 92542],
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),
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gen_config=dict(
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top_k=1,
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top_p=0.8,
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temperature=1.0,
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max_new_tokens=2000,
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),
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max_out_len=2000,
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max_seq_len=32768,
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batch_size=32,
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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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]
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