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About this paper
Raymond Li, Loubna Ben Allal, Yangtian Zi, Niklas Muennighoff, Denis Kocetkov, Chenghao Mou, Marc Marone, Christopher Akiki and 59 more
StarCoder and StarCoderBase are large language models for code developed by The BigCode community, demonstrating state-of-the-art performance among open-access models on Python code generation, achieving 33.6% pass@1 on HumanEval, and strong multi-language capabilities, all while integrating responsible AI practices.
Key insights
- Open, collaborative efforts like The BigCode community can yield competitive Code LLMs while prioritizing responsible AI development.
- Rigorous data governance, including PII redaction and permissive licensing, is feasible and critical for ethical LLM training.
- Architectural innovations like Multi-Query Attention and extended context lengths (8K tokens) are effective for scaling and improving Code LLM performance and efficiency.
Summary by alphaXiv.
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