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--- |
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language: |
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- en |
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license: apache-2.0 |
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datasets: |
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- nov3630/Data4RLCoder |
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--- |
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# Model Description |
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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. |
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- **Developed by:** Sun Yat-sen University & Huawei Cloud Computing Technologies Co., Ltd. |
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- **Shared by [Optional]:** Hugging Face |
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- **Model type:** Feature Engineering |
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- **Language(s) (NLP):** en |
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- **License:** Apache-2.0 |
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- **Related Models:** |
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- **Parent Model:** RoBERTa |
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- **Resources for more information:** |
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- [Associated Paper](https://arxiv.org/abs/2407.19487) |
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# Citation |
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**BibTeX:** |
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``` |
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@misc{wang2024rlcoderreinforcementlearningrepositorylevel, |
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title={RLCoder: Reinforcement Learning for Repository-Level Code Completion}, |
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author={Yanlin Wang and Yanli Wang and Daya Guo and Jiachi Chen and Ruikai Zhang and Yuchi Ma and Zibin Zheng}, |
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year={2024}, |
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eprint={2407.19487}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.SE}, |
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url={https://arxiv.org/abs/2407.19487}, |
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} |
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``` |
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# How to Get Started with the Model |
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Use the code below to get started with the model. |
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<details> |
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<summary> Click to expand </summary> |
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```python |
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from transformers import AutoTokenizer, AutoModel |
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tokenizer = AutoTokenizer.from_pretrained("nov3630/RLRetriever") |
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model = AutoModel.from_pretrained("nov3630/RLRetriever") |
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``` |
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</details> |
