Datasets:
Tasks:
Text Generation
Modalities:
Text
Formats:
parquet
Languages:
code
Size:
10K - 100K
ArXiv:
Tags:
code
License:
metadata
dataset_info:
features:
- name: commit
dtype: string
- name: old_file
dtype: string
- name: new_file
dtype: string
- name: old_contents
dtype: string
- name: new_contents
dtype: string
- name: subject
dtype: string
- name: message
dtype: string
- name: lang
dtype: string
- name: license
dtype: string
- name: repos
dtype: string
- name: ndiff
dtype: string
- name: instruction
dtype: string
- name: content
dtype: string
splits:
- name: train
num_bytes: 113752028
num_examples: 22602
download_size: 48124127
dataset_size: 113752028
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
task_categories:
- text-generation
tags:
- code
license: mit
pretty_name: CanItEdit
language:
- code
EditPackFT
EditPackFT is a dataset built for training LLMs on the task of instructional code editing. The mail columns are:
old_contents
the code before the editinstruction
the instruction to transform thebefore
code into theafter
codenew_contents
the code after the editcontent
a pre-formatted training window that can be used to train an LLM with prompts in the format of:<before><instruction><after>
This dataset has been filtered from CommitPackFT. For more detail, see our paper, and our GitHub repository.
Citation
If you use our work, please cite our paper as such:
@misc{cassano2023edit,
title={Can It Edit? Evaluating the Ability of Large Language Models to Follow Code Editing Instructions},
author={Federico Cassano and Luisa Li and Akul Sethi and Noah Shinn and Abby Brennan-Jones and Anton Lozhkov and Carolyn Jane Anderson and Arjun Guha},
year={2023},
eprint={2312.12450},
archivePrefix={arXiv},
primaryClass={cs.SE}
}