Add release contribution

configs/datasets/ARC_c/ARC_c_gen.py

+from mmengine.config import read_base
+
+with read_base():
+    from .ARC_c_gen_3f3039 import ARC_c_datasets  # noqa: F401, F403

configs/datasets/ARC_c/ARC_c_gen_3f3039.py

+from opencompass.openicl.icl_prompt_template import PromptTemplate
+from opencompass.openicl.icl_retriever import ZeroRetriever
+from opencompass.openicl.icl_inferencer import GenInferencer
+from opencompass.openicl.icl_evaluator import AccEvaluator
+from opencompass.datasets import ARCDataset
+
+ARC_c_reader_cfg = dict(
+    input_columns=["question", "textA", "textB", "textC", "textD"],
+    output_column="answerKey")
+
+ARC_c_infer_cfg = dict(
+    prompt_template=dict(
+        type=PromptTemplate,
+        template=dict(
+            round=[
+                dict(
+                    role="HUMAN",
+                    prompt=
+                    "Question: {question}\nA. {textA}\nB. {textB}\nC. {textC}\nD. {textD}\nAnswer:"
+                )
+            ], ),
+    ),
+    retriever=dict(type=ZeroRetriever),
+    inferencer=dict(type=GenInferencer),
+)
+
+ARC_c_eval_cfg = dict(
+    evaluator=dict(type=AccEvaluator),
+    pred_role="BOT",
+    pred_postprocessor=dict(type="first-capital"),
+)
+
+ARC_c_datasets = [
+    dict(
+        abbr="ARC-c",
+        type=ARCDataset,
+        path="./data/ARC/ARC-c/ARC-Challenge-Dev.jsonl",
+        reader_cfg=ARC_c_reader_cfg,
+        infer_cfg=ARC_c_infer_cfg,
+        eval_cfg=ARC_c_eval_cfg,
+    )
+]

configs/datasets/ARC_e/ARC_e_ppl_f86898.py

+from opencompass.openicl.icl_prompt_template import PromptTemplate
+from opencompass.openicl.icl_retriever import ZeroRetriever
+from opencompass.openicl.icl_inferencer import PPLInferencer
+from opencompass.openicl.icl_evaluator import AccEvaluator
+from opencompass.datasets import ARCDataset
+
+ARC_e_reader_cfg = dict(
+    input_columns=['question', 'textA', 'textB', 'textC', 'textD'],
+    output_column='answerKey')
+
+ARC_e_infer_cfg = dict(
+    prompt_template=dict(
+        type=PromptTemplate,
+        template={
+            "A":
+            dict(
+                round=[
+                    dict(role="HUMAN", prompt="Question: {question}\nAnswer: "),
+                    dict(role="BOT", prompt="{textA}")
+                ], ),
+            "B":
+            dict(
+                round=[
+                    dict(role="HUMAN", prompt="Question: {question}\nAnswer: "),
+                    dict(role="BOT", prompt="{textB}")
+                ], ),
+            "C":
+            dict(
+                round=[
+                    dict(role="HUMAN", prompt="Question: {question}\nAnswer: "),
+                    dict(role="BOT", prompt="{textC}")
+                ], ),
+            "D":
+            dict(
+                round=[
+                    dict(role="HUMAN", prompt="Question: {question}\nAnswer: "),
+                    dict(role="BOT", prompt="{textD}")
+                ], ),
+        }),
+    retriever=dict(type=ZeroRetriever),
+    inferencer=dict(type=PPLInferencer))
+
+ARC_e_eval_cfg = dict(evaluator=dict(type=AccEvaluator))
+
+ARC_e_datasets = [
+    dict(
+        type=ARCDataset,
+        abbr='ARC-e',
+        path='./data/ARC/ARC-e/ARC-Easy-Dev.jsonl',
+        reader_cfg=ARC_e_reader_cfg,
+        infer_cfg=ARC_e_infer_cfg,
+        eval_cfg=ARC_e_eval_cfg)
+]

configs/datasets/CLUE_CMRC/CLUE_CMRC_gen_220a83.py

+from opencompass.openicl.icl_prompt_template import PromptTemplate
+from opencompass.openicl.icl_retriever import ZeroRetriever
+from opencompass.openicl.icl_inferencer import GenInferencer
+from opencompass.openicl.icl_evaluator import EMEvaluator
+from opencompass.datasets import CMRCDataset
+
+CMRC_reader_cfg = dict(
+    input_columns=['question', 'context'], output_column='answers')
+
+CMRC_infer_cfg = dict(
+    prompt_template=dict(
+        type=PromptTemplate,
+        template="文章：{context}\n根据上文，回答如下问题： {question}\n答："),
+    retriever=dict(type=ZeroRetriever),
+    inferencer=dict(type=GenInferencer))
+
+CMRC_eval_cfg = dict(evaluator=dict(type=EMEvaluator), )
+
+CMRC_datasets = [
+    dict(
+        type=CMRCDataset,
+        abbr='CMRC_dev',
+        path='./data/CLUE/CMRC/dev.json',
+        reader_cfg=CMRC_reader_cfg,
+        infer_cfg=CMRC_infer_cfg,
+        eval_cfg=CMRC_eval_cfg),
+]

configs/datasets/CLUE_afqmc/CLUE_afqmc_ppl_c83c36.py

+from opencompass.openicl.icl_prompt_template import PromptTemplate
+from opencompass.openicl.icl_retriever import ZeroRetriever
+from opencompass.openicl.icl_inferencer import PPLInferencer
+from opencompass.openicl.icl_evaluator import AccEvaluator
+from opencompass.datasets import HFDataset
+
+afqmc_reader_cfg = dict(
+    input_columns=['sentence1', 'sentence2'],
+    output_column='label',
+    test_split='train')
+
+afqmc_infer_cfg = dict(
+    prompt_template=dict(
+        type=PromptTemplate,
+        template={
+            0:
+            dict(round=[
+                dict(
+                    role="HUMAN",
+                    prompt=
+                    "语句一：“{sentence1}”\n语句二：“{sentence2}”\n语句一与语句二是关于蚂蚁金融产品的疑问，两者所询问的内容是否完全一致？"
+                ),
+                dict(role="BOT", prompt="不完全一致")
+            ]),
+            1:
+            dict(round=[
+                dict(
+                    role="HUMAN",
+                    prompt=
+                    "语句一：“{sentence1}”\n语句二：“{sentence2}”\n语句一与语句二是关于蚂蚁金融产品的疑问，两者所询问的内容是否完全一致？"
+                ),
+                dict(role="BOT", prompt="完全一致")
+            ]),
+        }),
+    retriever=dict(type=ZeroRetriever),
+    inferencer=dict(type=PPLInferencer))
+
+afqmc_eval_cfg = dict(evaluator=dict(type=AccEvaluator))
+
+afqmc_datasets = [
+    dict(
+        type=HFDataset,
+        abbr='afqmc-dev',
+        path='json',
+        data_files='./data/CLUE/AFQMC/dev.json',
+        split='train',
+        reader_cfg=afqmc_reader_cfg,
+        infer_cfg=afqmc_infer_cfg,
+        eval_cfg=afqmc_eval_cfg),
+]

configs/datasets/CLUE_cmnli/CLUE_cmnli_ppl.py

+from mmengine.config import read_base
+
+with read_base():
+    from .CLUE_cmnli_ppl_1c652a import cmnli_datasets  # noqa: F401, F403

configs/datasets/CLUE_cmnli/CLUE_cmnli_ppl_991e1b.py

+from opencompass.openicl.icl_prompt_template import PromptTemplate
+from opencompass.openicl.icl_retriever import ZeroRetriever
+from opencompass.openicl.icl_inferencer import PPLInferencer
+from opencompass.openicl.icl_evaluator import AccEvaluator
+from opencompass.datasets import HFDataset
+
+cmnli_reader_cfg = dict(
+    input_columns=['sentence1', 'sentence2'],
+    output_column='label',
+    test_split='train')
+
+cmnli_infer_cfg = dict(
+    prompt_template=dict(
+        type=PromptTemplate,
+        template={
+            'contradiction':
+            dict(round=[
+                dict(
+                    role="HUMAN",
+                    prompt="阅读文章：{sentence1}\n根据上文，回答如下问题：{sentence2}？"),
+                dict(role="BOT", prompt="错")
+            ]),
+            'entailment':
+            dict(round=[
+                dict(
+                    role="HUMAN",
+                    prompt="阅读文章：{sentence1}\n根据上文，回答如下问题：{sentence2}？"),
+                dict(role="BOT", prompt="对")
+            ]),
+            'neutral':
+            dict(round=[
+                dict(
+                    role="HUMAN", prompt="如果{sentence1}为真，那么{sentence2}也为真吗？"),
+                dict(role="BOT", prompt="可能")
+            ]),
+        }),
+    retriever=dict(type=ZeroRetriever),
+    inferencer=dict(type=PPLInferencer))
+
+cmnli_eval_cfg = dict(evaluator=dict(type=AccEvaluator))
+
+cmnli_datasets = [
+    dict(
+        type=HFDataset,
+        abbr='cmnli',
+        path='json',
+        split='train',
+        data_files='./data/CLUE/cmnli/cmnli_public/dev.json',
+        reader_cfg=cmnli_reader_cfg,
+        infer_cfg=cmnli_infer_cfg,
+        eval_cfg=cmnli_eval_cfg)
+]

configs/datasets/CLUE_cmnli/CLUE_cmnli_ppl_b78ad4.py

+from opencompass.openicl.icl_prompt_template import PromptTemplate
+from opencompass.openicl.icl_retriever import ZeroRetriever
+from opencompass.openicl.icl_inferencer import PPLInferencer
+from opencompass.openicl.icl_evaluator import AccEvaluator
+from opencompass.datasets import HFDataset
+
+cmnli_reader_cfg = dict(
+    input_columns=['sentence1', 'sentence2'],
+    output_column='label',
+    test_split='train')
+
+cmnli_infer_cfg = dict(
+    prompt_template=dict(
+        type=PromptTemplate,
+        template={
+            'contradiction':
+            '阅读文章：{sentence1}\n根据上文，回答如下问题： {sentence2}？\n答：错',
+            'entailment': '阅读文章：{sentence1}\n根据上文，回答如下问题： {sentence2}？\n答：对',
+            'neutral': '如果{sentence1}为真，那么{sentence2}也为真吗?可能'
+        }),
+    retriever=dict(type=ZeroRetriever),
+    inferencer=dict(type=PPLInferencer))
+
+cmnli_eval_cfg = dict(evaluator=dict(type=AccEvaluator))
+
+cmnli_datasets = [
+    dict(
+        type=HFDataset,
+        abbr='cmnli',
+        path='json',
+        split='train',
+        data_files='./data/CLUE/cmnli/cmnli_public/dev.json',
+        reader_cfg=cmnli_reader_cfg,
+        infer_cfg=cmnli_infer_cfg,
+        eval_cfg=cmnli_eval_cfg)
+]

configs/datasets/CLUE_ocnli/CLUE_ocnli_gen_01899f.py

+from opencompass.openicl.icl_prompt_template import PromptTemplate
+from opencompass.openicl.icl_retriever import ZeroRetriever
+from opencompass.openicl.icl_inferencer import GenInferencer
+from opencompass.openicl.icl_evaluator import AccEvaluator
+from opencompass.datasets import cmnliDataset_V2
+
+ocnli_reader_cfg = dict(
+    input_columns=["sentence1", "sentence2"],
+    output_column="label",
+)
+
+# TODO: two prompt templates for ocnli
+ocnli_infer_cfg = dict(
+    prompt_template=dict(
+        type=PromptTemplate,
+        template=dict(round=[
+            dict(
+                role="HUMAN",
+                prompt=
+                "阅读文章：{sentence1}\n根据上文，回答如下问题：{sentence2}\nA. 对\nB. 错\nC. 可能\n请从“A”，“B”，“C”中进行选择。\n答："
+            ),
+        ]),
+    ),
+    retriever=dict(type=ZeroRetriever),
+    inferencer=dict(type=GenInferencer),
+)
+
+ocnli_eval_cfg = dict(
+    evaluator=dict(type=AccEvaluator),
+    pred_role="BOT",
+    pred_postprocessor=dict(type="first-capital"),
+)
+
+ocnli_datasets = [
+    dict(
+        abbr="ocnli",
+        type=cmnliDataset_V2,  # ocnli share the same format with cmnli
+        path="./data/CLUE/OCNLI/dev.json",
+        reader_cfg=ocnli_reader_cfg,
+        infer_cfg=ocnli_infer_cfg,
+        eval_cfg=ocnli_eval_cfg,
+    )
+]

configs/datasets/FewCLUE_bustm/FewCLUE_bustm_ppl_4f864a.py

+from opencompass.openicl.icl_prompt_template import PromptTemplate
+from opencompass.openicl.icl_retriever import ZeroRetriever
+from opencompass.openicl.icl_inferencer import PPLInferencer
+from opencompass.openicl.icl_evaluator import AccEvaluator
+from opencompass.datasets import HFDataset
+
+bustm_reader_cfg = dict(
+    input_columns=['sentence1', 'sentence2'],
+    output_column='label',
+    test_split='train')
+
+bustm_infer_cfg = dict(
+    prompt_template=dict(
+        type=PromptTemplate,
+        template={
+            0: "{sentence1}。\n{sentence2}。\n两句话说的毫不相关。",
+            1: "{sentence1}。\n{sentence2}。\n两句话说的一个意思。"
+        }),
+    retriever=dict(type=ZeroRetriever),
+    inferencer=dict(type=PPLInferencer))
+
+bustm_eval_cfg = dict(evaluator=dict(type=AccEvaluator))
+
+bustm_datasets = [
+    dict(
+        type=HFDataset,
+        abbr='bustm-dev',
+        path='json',
+        data_files='./data/FewCLUE/bustm/dev_few_all.json',
+        split='train',
+        reader_cfg=bustm_reader_cfg,
+        infer_cfg=bustm_infer_cfg,
+        eval_cfg=bustm_eval_cfg),
+    dict(
+        type=HFDataset,
+        abbr='bustm-test',
+        path='json',
+        data_files='./data/FewCLUE/bustm/test_public.json',
+        split='train',
+        reader_cfg=bustm_reader_cfg,
+        infer_cfg=bustm_infer_cfg,
+        eval_cfg=bustm_eval_cfg)
+]

configs/datasets/FewCLUE_chid/FewCLUE_chid_gen.py

+from mmengine.config import read_base
+
+with read_base():
+    from .FewCLUE_chid_gen_686c63 import chid_datasets  # noqa: F401, F403

configs/datasets/FewCLUE_cluewsc/FewCLUE_cluewsc_ppl.py

+from mmengine.config import read_base
+
+with read_base():
+    from .FewCLUE_cluewsc_ppl_2a9e61 import cluewsc_datasets  # noqa: F401, F403

configs/datasets/FewCLUE_csl/FewCLUE_csl_gen_1b0c02.py

+from opencompass.openicl.icl_prompt_template import PromptTemplate
+from opencompass.openicl.icl_retriever import ZeroRetriever
+from opencompass.openicl.icl_inferencer import GenInferencer
+from opencompass.openicl.icl_evaluator import AccEvaluator
+from opencompass.datasets import CslDataset_V2
+
+csl_reader_cfg = dict(
+    input_columns=["abst", "keywords"],
+    output_column="label",
+)
+
+csl_infer_cfg = dict(
+    prompt_template=dict(
+        type=PromptTemplate,
+        template=dict(round=[
+            dict(
+                role="HUMAN",
+                prompt=
+                "摘要：{abst}\n关键词：{keywords}\n上述关键词出现在学术期刊中是否恰当？\nA. 否\nB. 是\n请从”A“，”B“中进行选择。\n答："
+            )
+        ]),
+    ),
+    retriever=dict(type=ZeroRetriever),
+    inferencer=dict(type=GenInferencer),
+)
+
+csl_eval_cfg = dict(
+    evaluator=dict(type=AccEvaluator),
+    pred_role="BOT",
+    pred_postprocessor=dict(type="first-capital"),
+)
+
+csl_datasets = [
+    dict(
+        abbr="csl_dev",
+        type=CslDataset_V2,
+        path="./data/FewCLUE/csl/dev_few_all.json",
+        reader_cfg=csl_reader_cfg,
+        infer_cfg=csl_infer_cfg,
+        eval_cfg=csl_eval_cfg,
+    ),
+    dict(
+        abbr="csl_test",
+        type=CslDataset_V2,
+        path="./data/FewCLUE/csl/test_public.json",
+        reader_cfg=csl_reader_cfg,
+        infer_cfg=csl_infer_cfg,
+        eval_cfg=csl_eval_cfg,
+    ),
+]

configs/datasets/FewCLUE_eprstmt/FewCLUE_eprstmt_gen_d6d06d.py

+from opencompass.openicl.icl_prompt_template import PromptTemplate
+from opencompass.openicl.icl_retriever import ZeroRetriever
+from opencompass.openicl.icl_inferencer import GenInferencer
+from opencompass.openicl.icl_evaluator import AccEvaluator
+from opencompass.datasets import eprstmtDataset_V2
+
+eprstmt_reader_cfg = dict(
+    input_columns=["sentence"], output_column="label", test_split="train")
+
+eprstmt_infer_cfg = dict(
+    prompt_template=dict(
+        type=PromptTemplate,
+        template=dict(round=[
+            dict(
+                role="HUMAN",
+                prompt=
+                '内容： "{sentence}"。请对上述内容进行情绪分类。\nA. 积极\nB. 消极\n请从”A“，”B“中进行选择。\n答：'
+            ),
+        ]),
+    ),
+    retriever=dict(type=ZeroRetriever),
+    inferencer=dict(type=GenInferencer),
+)
+
+eprstmt_eval_cfg = dict(
+    evaluator=dict(type=AccEvaluator),
+    pred_role="BOT",
+    pred_postprocessor=dict(type="first-capital"),
+)
+
+eprstmt_datasets = [
+    dict(
+        abbr="eprstmt-dev",
+        type=eprstmtDataset_V2,
+        path="./data/FewCLUE/eprstmt/dev_few_all.json",
+        reader_cfg=eprstmt_reader_cfg,
+        infer_cfg=eprstmt_infer_cfg,
+        eval_cfg=eprstmt_eval_cfg,
+    ),
+    dict(
+        abbr="eprstmt-test",
+        type=eprstmtDataset_V2,
+        path="./data/FewCLUE/eprstmt/test_public.json",
+        reader_cfg=eprstmt_reader_cfg,
+        infer_cfg=eprstmt_infer_cfg,
+        eval_cfg=eprstmt_eval_cfg,
+    ),
+]

configs/datasets/FewCLUE_eprstmt/FewCLUE_eprstmt_ppl_d3c387.py

+from opencompass.openicl.icl_prompt_template import PromptTemplate
+from opencompass.openicl.icl_retriever import ZeroRetriever
+from opencompass.openicl.icl_inferencer import PPLInferencer
+from opencompass.openicl.icl_evaluator import AccEvaluator
+from opencompass.datasets import HFDataset
+
+eprstmt_reader_cfg = dict(
+    input_columns=['sentence'], output_column='label', test_split='train')
+
+eprstmt_infer_cfg = dict(
+    prompt_template=dict(
+        type=PromptTemplate,
+        template={
+            'Negative':
+            dict(round=[
+                dict(role='HUMAN', prompt='内容： "{sentence}"。情绪分类：'),
+                dict(role='BOT', prompt='消极。')
+            ]),
+            'Positive':
+            dict(round=[
+                dict(role='HUMAN', prompt='内容： "{sentence}"。情绪分类：'),
+                dict(role='BOT', prompt='积极。')
+            ]),
+        }),
+    retriever=dict(type=ZeroRetriever),
+    inferencer=dict(type=PPLInferencer))
+
+eprstmt_eval_cfg = dict(evaluator=dict(type=AccEvaluator))
+
+eprstmt_datasets = [
+    dict(
+        type=HFDataset,
+        abbr='eprstmt-dev',
+        path='json',
+        data_files='./data/FewCLUE/eprstmt/dev_few_all.json',
+        split='train',
+        reader_cfg=eprstmt_reader_cfg,
+        infer_cfg=eprstmt_infer_cfg,
+        eval_cfg=eprstmt_eval_cfg),
+    dict(
+        type=HFDataset,
+        abbr='eprstmt-test',
+        path='json',
+        data_files='./data/FewCLUE/eprstmt/test_public.json',
+        split='train',
+        reader_cfg=eprstmt_reader_cfg,
+        infer_cfg=eprstmt_infer_cfg,
+        eval_cfg=eprstmt_eval_cfg)
+]

configs/datasets/FewCLUE_tnews/FewCLUE_tnews_gen.py

+from mmengine.config import read_base
+
+with read_base():
+    from .FewCLUE_tnews_gen_8d59ba import tnews_datasets  # noqa: F401, F403

configs/datasets/PJExam/PJExam_gen_785c37.py

+from opencompass.openicl.icl_prompt_template import PromptTemplate
+from opencompass.openicl.icl_retriever import ZeroRetriever
+from opencompass.openicl.icl_inferencer import GenInferencer
+from opencompass.datasets import PJExamDataset, PJExamEvaluator
+
+PJExam_datasets = []
+for _name in [
+        'gk-2022-v1', 'gk-2022-v1-math', 'gk-2023-v1', 'gk-2023-v1-math',
+        'gk-2023-v2', 'gk-2023-v2-math', 'zk-2022-v1'
+]:
+    _hint = "请你做一道</major>选择题\n请你一步一步思考并将思考过程写在【解析】和<eoe>之间。你将从A，B，C，D中选出正确的答案，并写在【答案】和<eoa>之间。\n例如：【答案】A<eoa>\n完整的题目回答的格式如下：\n【解析】...<eoe>\n【答案】...<eoa>\n请你严格按照上述格式作答。\n题目如下：\n"
+    _reader_cfg = {
+        "input_columns": ['question'],
+        "output_column": 'std_ans',
+    },
+    _infer_cfg = {
+        "ice_template": {
+            "type": PromptTemplate,
+            "template": {
+                "round": [{
+                    "role": "HUMAN",
+                    "prompt": _hint + "{question}",
+                }]
+            },
+            "ice_token": "</E>"
+        },
+        "retriever": {
+            "type": ZeroRetriever
+        },
+        "inferencer": {
+            "type": GenInferencer,
+            "max_out_len": 1024,
+        }
+    }
+    _eval_cfg = {
+        "evaluator": {
+            "type": PJExamEvaluator
+        },
+        "pred_role": "BOT",
+        "ds_column": "eval_infos"
+    }
+    _dataset = {
+        "type": PJExamDataset,
+        "abbr": "PJExamDataset-" + _name,
+        "path": './data/PJExam',
+        "name": _name,
+        "reader_cfg": _reader_cfg,
+        "infer_cfg": _infer_cfg,
+        "eval_cfg": _eval_cfg,
+    }
+
+    PJExam_datasets.append(_dataset)
+
+del _name, _hint, _reader_cfg, _infer_cfg, _eval_cfg, _dataset

configs/datasets/SuperGLUE_AX_b/SuperGLUE_AX_b_ppl_a65d62.py

+from opencompass.openicl.icl_prompt_template import PromptTemplate
+from opencompass.openicl.icl_retriever import ZeroRetriever
+from opencompass.openicl.icl_inferencer import PPLInferencer
+from opencompass.openicl.icl_evaluator import AccEvaluator
+from opencompass.datasets import HFDataset
+
+AX_b_reader_cfg = dict(
+    input_columns=['sentence1', 'sentence2'],
+    output_column='label',
+    test_split='train')
+
+AX_b_infer_cfg = dict(
+    prompt_template=dict(
+        type=PromptTemplate,
+        template={
+            'entailment': '{sentence1}?entailment, {sentence2}',
+            'not_entailment': '{sentence1}?not_entailment, {sentence2}'
+        }),
+    retriever=dict(type=ZeroRetriever),
+    inferencer=dict(type=PPLInferencer))
+
+AX_b_eval_cfg = dict(evaluator=dict(type=AccEvaluator))
+
+AX_b_datasets = [
+    dict(
+        type=HFDataset,
+        abbr='AX_b',
+        path='json',
+        data_files='./data/SuperGLUE/AX-b/AX-b.jsonl',
+        split='train',
+        reader_cfg=AX_b_reader_cfg,
+        infer_cfg=AX_b_infer_cfg,
+        eval_cfg=AX_b_eval_cfg)
+]

configs/datasets/SuperGLUE_AX_g/SuperGLUE_AX_g_ppl.py

+from mmengine.config import read_base
+
+with read_base():
+    from .SuperGLUE_AX_g_ppl_8d9bf9 import AX_g_datasets  # noqa: F401, F403

configs/datasets/SuperGLUE_AX_g/SuperGLUE_AX_g_ppl_d489ee.py

+from opencompass.openicl.icl_prompt_template import PromptTemplate
+from opencompass.openicl.icl_retriever import ZeroRetriever
+from opencompass.openicl.icl_inferencer import PPLInferencer
+from opencompass.openicl.icl_evaluator import AccEvaluator
+from opencompass.datasets import HFDataset
+
+AX_g_reader_cfg = dict(
+    input_columns=['hypothesis', 'premise'],
+    output_column='label',
+    test_split='train')
+
+AX_g_infer_cfg = dict(
+    prompt_template=dict(
+        type=PromptTemplate,
+        template={
+            'entailment': '{premise}?entailment, {hypothesis}',
+            'not_entailment': '{premise}?not_entailment, {hypothesis}'
+        }),
+    retriever=dict(type=ZeroRetriever),
+    inferencer=dict(type=PPLInferencer))
+
+AX_g_eval_cfg = dict(evaluator=dict(type=AccEvaluator))
+
+AX_g_datasets = [
+    dict(
+        type=HFDataset,
+        abbr='AX_g',
+        path='json',
+        data_files='./data/SuperGLUE/AX-g/AX-g.jsonl',
+        split='train',
+        reader_cfg=AX_g_reader_cfg,
+        infer_cfg=AX_g_infer_cfg,
+        eval_cfg=AX_g_eval_cfg)
+]