RLRetriever

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

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.

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from transformers import AutoTokenizer, AutoModel
 
tokenizer = AutoTokenizer.from_pretrained("nov3630/RLRetriever")
 
model = AutoModel.from_pretrained("nov3630/RLRetriever")
 

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