  The rapid development of large language models has revolutionized code
intelligence in software development. However, the predominance of
closed-source models has restricted extensive research and development. To
address this, we introduce the DeepSeek-Coder series, a range of open-source
code models with sizes from 1.3B to 33B, trained from scratch on 2 trillion
tokens. These models are pre-trained on a high-quality project-level code
corpus and employ a fill-in-the-blank task with a 16K window to enhance code
generation and infilling. Our extensive evaluations demonstrate that
DeepSeek-Coder not only achieves state-of-the-art performance among open-source
code models across multiple benchmarks but also surpasses existing
closed-source models like Codex and GPT-3.5. Furthermore, DeepSeek-Coder models
are under a permissive license that allows for both research and unrestricted
commercial use.
