Qwen2.5-Coder-1.5B

1.5B parameter code generation model in the Qwen2.5-Coder series

CommonProductProgrammingCode GenerationCode Reasoning

Qwen2.5-Coder-1.5B is a large language model in the Qwen2.5-Coder series, focusing on code generation, reasoning, and debugging. Built upon the robust Qwen2.5 architecture, this model has significantly expanded the training tokens to 5.5 trillion, incorporating source code, textual code bases, synthetic data, and more, making it a leader among open-source code LLMs, rivaling GPT-4o's coding capabilities. Moreover, Qwen2.5-Coder-1.5B has enhanced its mathematical and general capabilities, providing a more comprehensive foundation for practical applications such as code agents.

Code Generation: Significantly improves code generation ability
aiding developers in quickly writing and optimizing code.
Code Reasoning: Enhances the model's understanding of code logic
improving accuracy in code analysis and reasoning.
Code Debugging: Assists developers in identifying and fixing errors in code
thereby improving code quality.
Mathematical and General Capabilities: Strengthens both programming and applied mathematics/general domains.
32
768 Token Context Length: Supports longer code segments
improving the model's understanding of complex code structures.

\Target audience includes developers
programming enthusiasts
and professionals who require code generation and optimization. Qwen2.5-Coder-1.5B significantly enhances their development efficiency and reduces errors by offering powerful capabilities for code generation
reasoning
and debugging

Developers generate new code snippets using Qwen2.5-Coder-1.5B to accelerate project development.
During code reviews
Qwen2.5-Coder-1.5B is utilized to analyze code logic and identify potential issues.
In the education sector
teachers use Qwen2.5-Coder-1.5B to assist students in understanding complex programming concepts and code structures.

1. Visit the Hugging Face platform and search for the Qwen2.5-Coder-1.5B model.
2. Read the model documentation to understand its specific features and usage limitations.
3. Select the appropriate code generation
reasoning
or debugging task based on your project needs.

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Visit Duration

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