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---
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> |