Delete loading script

LongBench.py

@@ -1,127 +0,0 @@
-# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-import os
-
-import datasets
-import json
-
-
-_DESCRIPTION = """\
-LongBench is a comprehensive benchmark for multilingual and multi-task purposes, with the goal to fully measure and evaluate the ability of pre-trained language models to understand long text. This dataset consists of twenty different tasks, covering key long-text application scenarios such as multi-document QA, single-document QA, summarization, few-shot learning, synthetic tasks, and code completion.
-"""
-
-_HOMEPAGE = "https://github.com/THUDM/LongBench"
-
-
-_URL = r"https://huggingface.co/datasets/THUDM/LongBench/resolve/main/data.zip"
-
-task_list = [
-    "narrativeqa",
-    "qasper",
-    "multifieldqa_en",
-    "multifieldqa_zh",
-    "hotpotqa",
-    "2wikimqa",
-    "musique",
-    "dureader",
-    "gov_report",
-    "qmsum",
-    "multi_news",
-    "vcsum",
-    "trec",
-    "triviaqa",
-    "samsum",
-    "lsht",
-    "passage_count",
-    "passage_retrieval_en",
-    "passage_retrieval_zh",
-    "lcc",
-    "repobench-p",
-    "qasper_e",
-    "multifieldqa_en_e",
-    "hotpotqa_e",
-    "2wikimqa_e",
-    "gov_report_e",
-    "multi_news_e",
-    "trec_e",
-    "triviaqa_e",
-    "samsum_e",
-    "passage_count_e",
-    "passage_retrieval_en_e",
-    "lcc_e",
-    "repobench-p_e"
-]
-
-
-class LongBenchConfig(datasets.BuilderConfig):
-    def __init__(self, **kwargs):
-        super().__init__(version=datasets.Version("1.0.0"), **kwargs)
-
-
-class LongBench(datasets.GeneratorBasedBuilder):
-    BUILDER_CONFIGS = [
-        LongBenchConfig(
-            name=task_name,
-        )
-        for task_name in task_list
-    ]
-
-    def _info(self):
-        features = datasets.Features(
-            {
-                "input": datasets.Value("string"), 
-                "context": datasets.Value("string"), 
-                "answers": [datasets.Value("string")], 
-                "length": datasets.Value("int32"), 
-                "dataset": datasets.Value("string"), 
-                "language": datasets.Value("string"), 
-                "all_classes": [datasets.Value("string")],
-                "_id": datasets.Value("string"), 
-            }
-        )
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=features,
-            homepage=_HOMEPAGE,
-        )
-
-    def _split_generators(self, dl_manager):
-        data_dir = dl_manager.download_and_extract(_URL)
-        task_name = self.config.name
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={
-                    "filepath": os.path.join(
-                        data_dir, "data", f"{task_name}.jsonl"
-                    ),
-                },
-            )
-        ]
-
-    def _generate_examples(self, filepath):
-        with open(filepath, encoding="utf-8") as f:
-            for idx, line in enumerate(f):
-                key = f"{self.config.name}-{idx}"
-                item = json.loads(line)
-                yield key, {
-                    "input": item["input"],
-                    "context": item["context"],
-                    "answers": item["answers"],
-                    "length": item["length"],
-                    "dataset": item["dataset"],
-                    "language": item["language"],
-                    "_id": item["_id"],
-                    "all_classes": item["all_classes"],
-                }