Datasets:
Tasks:
Text Generation
Modalities:
Text
Formats:
json
Sub-tasks:
language-modeling
Languages:
English
Size:
10K<n<100K
ArXiv:
Tags:
License:
| # 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 json | |
| import os | |
| import datasets | |
| import pandas as pd | |
| from datasets import DatasetInfo, DownloadManager | |
| _CITATION = """\ | |
| """ | |
| _DESCRIPTION = """\ | |
| """ | |
| _LICENSE = "" | |
| _URL = r"https://huggingface.co/datasets/hkust-nlp/llm-compression/resolve/main/data.zip" | |
| Task_list = [ | |
| "python", | |
| "cc", | |
| "arxiv_math", | |
| ] | |
| class LlmCompressionConfig(datasets.BuilderConfig): | |
| def __init__(self, **kwargs): | |
| super().__init__(version=datasets.Version("1.0.0"), **kwargs) | |
| class LlmCompression(datasets.GeneratorBasedBuilder): | |
| BUILDER_CONFIGS = [ | |
| LlmCompressionConfig( | |
| name=task_name, | |
| ) | |
| for task_name in Task_list | |
| ] | |
| def _info(self): | |
| features = datasets.Features( | |
| { | |
| "content": datasets.Value("string"), | |
| "subset": datasets.Value("string"), | |
| "meta": datasets.features.Value("string"), | |
| } | |
| ) | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, | |
| features=features, | |
| license=_LICENSE, | |
| ) | |
| def _split_generators(self, dl_manager: DownloadManager): | |
| 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, f"{task_name}.jsonl")}) | |
| ] | |
| def _generate_examples(self, filepath): | |
| """Yields examples.""" | |
| with open(filepath,encoding="utf-8") as f: | |
| for id_, row in enumerate(f): | |
| cur_data = json.loads(row) | |
| yield id_, { | |
| "content": cur_data["content"], | |
| "subset": cur_data["subset"], | |
| "meta": str(cur_data["meta"]), | |
| } | |