README.md

---
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:
1. `old_contents` the code before the edit
2. `instruction` the instruction to transform the `before` code into the `after` code
3. `new_contents` the code after the edit
4. `content` 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](https://arxiv.org/abs/2312.12450), and our [GitHub repository](https://github.com/nuprl/CanItEdit/tree/main/editpackft).

## Citation
If you use our work, please cite our paper as such:
```
@inproceedings{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},
      booktitle={The First International Workshop on Large Language Model for Code},
      year={2024},
      url={https://arxiv.org/abs/2312.12450}
}
```