Lingma SWE-GPT

An open-source large language model specifically designed for software improvement.

CommonProductProgrammingOpen SourceArtificial Intelligence

Lingma SWE-GPT is an open-source large language model focused on tasks within the software engineering domain, aimed at providing intelligent development support. The model is based on the Qwen series foundational models and has undergone additional training to enhance its capabilities in complex software engineering tasks. It ranks highly on authoritative leaderboards for intelligent agents in software engineering, making it suitable for development teams and researchers seeking automation in software enhancement.

Provides intelligent code generation and repair suggestions.
Supports automation for complex software engineering tasks.
Trained on data from the software engineering development process to enhance model specialization.
Achieves excellent resolution and fault localization rates on the SWE-bench leaderboard.
Supports integration and deployment in various development environments.
Offers detailed documentation and examples to facilitate quick onboarding for developers.
Supports virtual environment configurations
simplifying the model installation and usage process.
Can be invoked via API for easy integration with existing systems.

This product is designed for software developers
researchers
and technical teams
especially those who require automation in software improvement and intelligent development support. With its powerful model capabilities
Lingma SWE-GPT helps users enhance development efficiency

Utilize Lingma SWE-GPT for automated code generation to boost development efficiency.
Employ the model for code reviews and fixes to minimize human errors.
Use in educational settings to help students understand software engineering concepts and practices.

Visit the product page and clone the repository: `git clone https://github.com/LingmaTongyi/SWESynInfer.git`.
Navigate to the project directory and create a virtual environment: `cd SWESynInfer`
`conda env create -f environment.yml`.
Activate the virtual environment: `conda activate swesyninfer`.
Set the model path and run the testing script: `python scripts/1_change_testbed_path.py YOUR_ABSOLUTE_PATH/SWESynInfer/SWE-bench/repos/testbed`.

Visit

Lingma SWE-GPT Visit Over Time

Monthly Visits

494758773

Bounce Rate

37.69%

Page per Visit

5.7

Visit Duration

00:06:29

Lingma SWE-GPT Visit Trend

Lingma SWE-GPT Visit Geography

Lingma SWE-GPT Traffic Sources

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