DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence
About
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.
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Mathematical Reasoning | GSM8K | Accuracy60.7 | 983 | |
| Code Generation | HumanEval | Pass@185.4 | 850 | |
| Mathematical Reasoning | GSM8K (test) | Accuracy58.7 | 751 | |
| Mathematical Reasoning | MATH | -- | 643 | |
| Code Generation | HumanEval (test) | Pass@179.3 | 444 | |
| Mathematical Reasoning | SVAMP | Accuracy71.6 | 368 | |
| Multitask Language Understanding | MMLU (test) | Accuracy34 | 303 | |
| Code Generation | MBPP (test) | Pass@170 | 276 | |
| Mathematical Reasoning | ASDIV | Accuracy0.767 | 221 | |
| Mathematical Reasoning | MAWPS | Accuracy93.3 | 219 |