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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
34 lines
876 B
Python
34 lines
876 B
Python
from opencompass.models import HuggingFaceCausalLM
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_meta_template = dict(
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begin='###',
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round=[
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dict(role='HUMAN', begin='Human: ', end='###'),
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dict(role='BOT', begin='Assistant: ', end='</s>', 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='aquilachat2-34b-16k-hf',
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path="BAAI/AquilaChat2-34B-16K",
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tokenizer_path='BAAI/AquilaChat2-34B-16K',
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model_kwargs=dict(
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device_map='auto',
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trust_remote_code=True,
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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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trust_remote_code=True,
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use_fast=False,
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),
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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=8,
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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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