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---
title: README
emoji: πŸ“‰
colorFrom: yellow
colorTo: indigo
sdk: static
pinned: false
---

# RepoFusion: Training Code Models to Understand Your Repository
Disha Shrivastava, Denis Kocetkov, Harm de Vries, Dzmitry Bahdanau, Torsten Scholak

This space contains the released resources for our paper [RepoFusion: Training Code Models to Understand Your Repository](https://arxiv.org/abs/2306.10998). A block diagram of our approach can be found below. For more details, refer to the paper.

![block diagram](block_diagram.png)

## Data
Stack-Repo can be accessed via the [Datasets](https://huggingface.co/datasets/RepoFusion/Stack-Repo) section of this space. Please see the [README](https://huggingface.co/datasets/RepoFusion/Stack-Repo) for complete details.

## Trained Checkpoints
The trained checkpoints can be downloaded from the [Models](https://huggingface.co/RepoFusion/trained_checkpoints). Please see the [README](https://huggingface.co/RepoFusion/trained_checkpoints) for complete details.

## Code
The code for training and evaluating RepoFusion, finetuning CodeT5, and details of how to run the scripts can be found [here](https://github.com/ServiceNow/RepoFusion)

## Citation
```
@article{shrivastava2023repofusion,
  title={RepoFusion: Training Code Models to Understand Your Repository},
  author={Shrivastava, Disha and Kocetkov, Denis and de Vries, Harm and Bahdanau, Dzmitry and Scholak, Torsten},
  journal={arXiv preprint arXiv:2306.10998},
  year={2023}
}
```