💻 programming

Qwen2.5-Coder-32B-Instruct-GPTQ-Int8

Open source code generation language model

#code generation
#Programming assistance
#Open source model
#Long text processing
#Quantitative techniques
Qwen2.5-Coder-32B-Instruct-GPTQ-Int8

Product Details

Qwen2.5-Coder-32B-Instruct-GPTQ-Int8 is a large language model optimized for code generation in the Qwen series. It has 3.2 billion parameters and supports long text processing. It is one of the most advanced models in the field of open source code generation. The model has been further trained and optimized based on Qwen2.5, which not only has significant improvements in code generation, reasoning and repair, but also maintains advantages in mathematics and general capabilities. The model uses GPTQ 8-bit quantization technology to reduce model size and improve operating efficiency.

Main Features

1
Code generation: Significantly improve code generation capabilities to match the coding capabilities of GPT-4o.
2
Code reasoning: Enhance code understanding capabilities to help developers better understand and optimize code.
3
Code Repair: Assist developers to find and fix errors in the code.
4
Long text support: Supports long text processing up to 128K tokens.
5
Quantification technology: Use GPTQ 8-bit quantification technology to reduce model size and improve operating efficiency.
6
High performance: Adapt to different development needs while maintaining high performance.
7
Open source: As an open source model, it is freely available for developers to use and further research.

How to Use

1
1. Visit the Hugging Face website and search for the Qwen2.5-Coder-32B-Instruct-GPTQ-Int8 model.
2
2. Import the required libraries and modules according to the code examples provided on the page.
3
3. Load the model and tokenizer, and prepare the input prompt.
4
4. Convert the prompt into an input format that the model can understand.
5
5. Use the model to generate code or perform code reasoning.
6
6. Get the model output and process it further as needed or use the generated code directly.

Target Users

The target audience is developers, programming enthusiasts, and teams that need code generation and optimization. This model is particularly suitable for software development projects that require rapid development and code quality assurance due to its powerful code generation and understanding capabilities.

Examples

Developers can use this model to quickly generate code for sorting algorithms.

During the code review process, use models to reason about code logic and improve code quality.

When encountering complex bugs, use models to assist in locating and repairing code problems.

Quick Access

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