Qwen2.5-Coder-32B

The open-source code generation model in the Qwen2.5-Coder series with the most parameters.

CommonProductProgrammingCode GenerationCode Reasoning

Qwen2.5-Coder-32B is a code generation model based on Qwen2.5, featuring 32 billion parameters, making it one of the largest open-source code language models available today. It shows significant improvements in code generation, reasoning, and fixing, capable of handling long texts up to 128K tokens, which is suitable for practical applications such as code assistants. The model also maintains advantages in mathematical and general capabilities, supporting long text processing, thus serving as a powerful assistant for developers in code development.

Code Generation: Significantly enhances code generation capabilities
matching the coding ability of GPT-4o.
Code Reasoning: Improves code understanding and reasoning capabilities
assisting developers in better understanding and maintaining code.
Code Fixing: Helps developers fix errors within the code
improving code quality.
Long Text Support: Capable of handling long texts up to 128K tokens
ideal for large projects.
Mathematical and General Capabilities: Maintains advantages in programming while also possessing capabilities in mathematics and general fields.
Based on Transformers Architecture: Utilizes advanced Transformers architecture including RoPE

\Target audience includes developers
programmers
and software engineers. Qwen2.5-Coder-32B is suitable for them as it offers powerful code generation
reasoning
and fixing capabilities

Developers use Qwen2.5-Coder-32B to generate new code snippets
enhancing development efficiency.
Software engineers utilize the model to fix existing errors in the code
reducing debugging time.
Teams use the model as a code review tool to identify potential code issues early.

1. Visit the Hugging Face platform and search for the Qwen2.5-Coder-32B model.
2. Read the model documentation to understand how to configure and use the model.
3. Adjust model parameters based on project needs
especially the YaRN configuration for handling long texts.
4. Use the API provided by Hugging Face or integrate the model into your local development environment.

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