README.md

---
library_name: transformers
datasets:
- nuprl/EditPackFT-Multi
---

EditCoder-Multi-6.7b (version 1) is a fine-tuned version of [DeepSeek Coder](deepseek-ai/deepseek-coder-6.7b-base) (base model, 6.7b parameters) for instructional code editing.
We utilize [EditPackFT-Multi](https://huggingface.co/datasets/nuprl/EditPackFT-Multi) as our fine-tuning dataset. The model is trained on a variety of different languages.

More information can be found on [our paper](https://arxiv.org/abs/2312.12450).

## 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}
}
```

# Prompt
The model has been trained on the following prompt format:
```
## Code Before:
{before}
## Instruction:
{instruction}
## Code After:
{after}
```

Here is a python function that can be used for formatting the prompt correctly:
```py
def edit_prompt(old, instr):
    before = f"""## Code Before:\n{old}\n"""
    instr = f"""## Instruction:\n{instr}\n"""
    after = f"""## Code After:\n"""
    return before + instr + after
```

# Train Your Own EditCoder
We provide the full pipeline that was used for training our own edit-coder model.
The pipeline and instructions can be found on our [GitHub repository](https://github.com/nuprl/CanItEdit/tree/main/editcoder).