EditCoder-6.7b-v1 / README.md
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---
language:
- code
datasets:
- nuprl/EditPackFT
library_name: transformers
pipeline_tag: text2text-generation
tags:
- code
model-index:
- name: EditCoder-6.7b-v1
results:
- task:
type: text-generation
dataset:
type: nuprl/CanItEdit
name: CanItEdit Descriptive
metrics:
- name: pass@1
type: pass@1
value: 0.4815
verified: false
- task:
type: text-generation
dataset:
type: nuprl/CanItEdit
name: CanItEdit Lazy
metrics:
- name: pass@1
type: pass@1
value: 0.3696
verified: false
---
EditCoder-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](https://huggingface.co/datasets/nuprl/EditPackFT) as our fine-tuning dataset, and we show state-of-the-art performance among non-distilled open source models
for code editing, using the [CanItEdit](https://huggingface.co/datasets/nuprl/CanItEdit) benchmark.
More information can be found on [our paper](https://arxiv.org/abs/2312.12450).
**NOTE: This is the model trained on EditPackFT, not Commits2023FT. We are working on releasing that one soon.**
## 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).