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Qwen2.5 Coder 1.5B
Overview :
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.
Target Users :
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, making it an essential tool in the programming field.
Use Cases
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.
Features
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.
Transformer-based Architecture: Utilizes advanced transformer architecture, including RoPE, SwiGLU, and RMSNorm technologies to enhance model performance.
1.54B Parameter Count: A substantial number of parameters enable the model to capture richer code patterns and relationships.
How to Use
1. Visit the Hugging Face platform and search for the Qwen2.5-Coder-1.5B model.
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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.
4. Use the API provided by Hugging Face or download the model to integrate it into your development environment.
5. Prepare the corresponding code or text data as required by the model's input specifications.
6. Submit the data to the model to obtain the generated code or analysis results.
7. Optimize the code or address issues based on the model's output.
8. Continue to iterate and optimize until satisfactory results are achieved.
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