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EditCoder-6.7b (version 1) is a fine-tuned version of DeepSeek Coder (base model, 6.7b parameters) for instructional code editing. We utilize 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 benchmark.

More information can be found on our paper. 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:

@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}
}

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:

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.

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Dataset used to train nuprl/EditCoder-6.7b-v1

Collection including nuprl/EditCoder-6.7b-v1

Evaluation results