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google/code_x_glue_tt_text_to_text

Dataset Card for "code_x_glue_tt_text_to_text" Dataset Summary CodeXGLUE text-to-text dataset, available at https://github.com/microsoft/CodeXGLUE/tree/main/Text-Text/text-to-text The dataset we use is crawled and filtered from Microsoft Documentation, whose document located at https://github.com/MicrosoftDocs/. Supported Tasks and Leaderboards machine-translation: The dataset can be used to train a model for translating Technical documentation… See the full description on the dataset page: https://huggingface.co/datasets/google/code_x_glue_tt_text_to_text.

sourceHugging Facec-udaupdated 3y agoView on Hugging Face
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Dataset Card

Dataset Card for "codexgluetttexttotext"

Table of Contents

Dataset Description

  • Homepage: https://github.com/microsoft/CodeXGLUE/tree/main/Text-Text/text-to-text
  • Paper: https://arxiv.org/abs/2102.04664

Dataset Summary

CodeXGLUE text-to-text dataset, available at https://github.com/microsoft/CodeXGLUE/tree/main/Text-Text/text-to-text

The dataset we use is crawled and filtered from Microsoft Documentation, whose document located at https://github.com/MicrosoftDocs/.

Supported Tasks and Leaderboards

  • machine-translation: The dataset can be used to train a model for translating Technical documentation between languages.

Languages

daen, lven, noen, zhen

Dataset Structure

Data Instances

da_en

An example of 'test' looks as follows.

{
    "id": 0, 
    "source": "4 . K\u00f8r modellen , og udgiv den som en webtjeneste .\n", 
    "target": "4 . Run the model , and publish it as a web service .\n"
}
lv_en

An example of 'train' looks as follows.

{
    "id": 0, 
    "source": "title : Pakalpojumu objektu izveide\n", 
    "target": "title : Create service objects\n"
}
no_en

An example of 'validation' looks as follows.

{
    "id": 0, 
    "source": "2 . \u00c5pne servicevaren du vil definere komponenter fra en stykkliste for .\n", 
    "target": "2 . Open the service item for which you want to set up components from a BOM .\n"
}
zh_en

An example of 'validation' looks as follows.

{
    "id": 0, 
    "source": "& # 124 ; MCDUserNotificationReadStateFilterAny & # 124 ; 0 & # 124 ; \u5305\u62ec \u901a\u77e5 , \u800c \u4e0d \u8003\u8651 \u8bfb\u53d6 \u72b6\u6001 \u3002 & # 124 ;\n", 
    "target": "| MCDUserNotificationReadStateFilterAny | 0 | Include notifications regardless of read state . |\n"
}

Data Fields

In the following each data field in go is explained for each config. The data fields are the same among all splits.

daen, lven, noen, zhen
field nametypedescription
idint32The index of the sample
sourcestringThe source language version of the text
targetstringThe target language version of the text

Data Splits

nametrainvalidationtest
da_en4270110001000
lv_en1874910001000
no_en4432210001000
zh_en5015410001000

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

[More Information Needed]

Annotations

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

https://github.com/microsoft, https://github.com/madlag

Licensing Information

Computational Use of Data Agreement (C-UDA) License.

Citation Information

@article{DBLP:journals/corr/abs-2102-04664,
  author    = {Shuai Lu and
               Daya Guo and
               Shuo Ren and
               Junjie Huang and
               Alexey Svyatkovskiy and
               Ambrosio Blanco and
               Colin B. Clement and
               Dawn Drain and
               Daxin Jiang and
               Duyu Tang and
               Ge Li and
               Lidong Zhou and
               Linjun Shou and
               Long Zhou and
               Michele Tufano and
               Ming Gong and
               Ming Zhou and
               Nan Duan and
               Neel Sundaresan and
               Shao Kun Deng and
               Shengyu Fu and
               Shujie Liu},
  title     = {CodeXGLUE: {A} Machine Learning Benchmark Dataset for Code Understanding
               and Generation},
  journal   = {CoRR},
  volume    = {abs/2102.04664},
  year      = {2021}
}

Contributions

Thanks to @madlag (and partly also @ncoop57) for adding this dataset.