---
language:
- en
license: apache-2.0
datasets:
- nov3630/Data4RLCoder
---

# Model Description
RLRetriever is a retriever for repository-level code completion which disregard seemingly useful yet ultimately unhelpful reference code snippets, focusing on those more likely to contribute to accurate code generation.
 
- **Developed by:** Sun Yat-sen University & Huawei Cloud Computing Technologies Co., Ltd. 
- **Shared by [Optional]:** Hugging Face
- **Model type:** Feature Engineering
- **Language(s) (NLP):** en
- **License:** Apache-2.0
- **Related Models:**
  - **Parent Model:** RoBERTa
- **Resources for more information:**
    - [Associated Paper](https://arxiv.org/abs/2407.19487)

 
# Citation
 
**BibTeX:**
```
@misc{wang2024rlcoderreinforcementlearningrepositorylevel,
      title={RLCoder: Reinforcement Learning for Repository-Level Code Completion}, 
      author={Yanlin Wang and Yanli Wang and Daya Guo and Jiachi Chen and Ruikai Zhang and Yuchi Ma and Zibin Zheng},
      year={2024},
      eprint={2407.19487},
      archivePrefix={arXiv},
      primaryClass={cs.SE},
      url={https://arxiv.org/abs/2407.19487}, 
}
```

 
# Get Started
 
Use the code below to get started with the model.
 
<details>
<summary> Click to expand </summary>

```python
from transformers import AutoTokenizer, AutoModel
 
tokenizer = AutoTokenizer.from_pretrained("nov3630/RLRetriever")
 
model = AutoModel.from_pretrained("nov3630/RLRetriever")
 
 ```
</details>