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43 lines
1.2 KiB
Python
43 lines
1.2 KiB
Python
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from opencompass.openicl.icl_prompt_template import PromptTemplate
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from opencompass.openicl.icl_retriever import ZeroRetriever
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from opencompass.openicl.icl_inferencer import GenInferencer
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from opencompass.datasets import MBPPDataset, MBPPEvaluator2
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mbpp_reader_cfg = dict(
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input_columns=['text', 'test_list'], output_column='test_list_2')
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# This prompt is used for WizardLMCode series
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# You can use other config file for basic 3-shot generation
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mbpp_infer_cfg = dict(
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prompt_template=dict(
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type=PromptTemplate,
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template=dict(round=[
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dict(
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role='HUMAN',
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prompt=
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"""Below is an instruction that describes a task. Write a response that appropriately completes the request.
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### Instruction:
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Create a Python script for this problem:
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{text}
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Test examples:
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{test_list}
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### Response:"""),
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])),
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retriever=dict(type=ZeroRetriever),
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inferencer=dict(type=GenInferencer, max_out_len=512))
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mbpp_eval_cfg = dict(evaluator=dict(type=MBPPEvaluator2), pred_role="BOT")
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mbpp_datasets = [
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dict(
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type=MBPPDataset,
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abbr='mbpp',
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path='./data/mbpp/mbpp.jsonl',
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reader_cfg=mbpp_reader_cfg,
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infer_cfg=mbpp_infer_cfg,
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eval_cfg=mbpp_eval_cfg)
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]
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