DeepSeek‐Coder V1 - amosproj/amos2025ss04-ai-driven-testing GitHub Wiki
DeepSeek-Coder-V1 is an open-source large language model developed by DeepSeek-AI, specifically optimized for code generation and understanding. It is released under a permissive MIT license, allowing both research and commercial usage.
🔍 Overview
DeepSeek-Coder-V1 was trained from scratch on a massive corpus of around 2 trillion tokens, composed of 87% code and 13% natural language [1]. This training enables the model to handle a broad range of programming tasks, from code generation and completion to infilling and explanation.
🔧 Key Features
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Wide Language Support:
Supports 87 programming languages, including Python, Java, C++, JavaScript, Go, Rust, HTML, SQL, Bash, and many more. -
Context Window:
Processes up to 16K tokens, making it well-suited for large codebases and long coding tasks. -
Multiple Model Sizes:
Available in different sizes to accommodate different hardware setups:- 1.3B parameters
- 5.7B parameters
- 6.7B parameters
- 33B parameters
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Fine-Tuning Support:
The official GitHub repository also provides fine-tuning versions of DeepSeek-Coder-V1, enabling users to adapt the model to their own datasets and specific tasks [2]. -
State-of-the-Art Performance:
Achieves strong results in open-source benchmarks for code intelligence, outperforming many older models like Codex and GPT-3.5 in various tasks.
🧠 Architecture
DeepSeek-Coder-V1 is built on a standard transformer architecture, emphasizing simplicity, efficiency, and broad compatibility.