internlm/SWE-Fixer-Retriever-7B
The internlm/SWE-Fixer-Retriever-7B is a 7.6 billion parameter language model, fine-tuned from Qwen2.5-7B, developed by InternLM. It is specifically designed as a code file retriever component within the SWE-Fixer pipeline for addressing GitHub issues. This model excels at identifying relevant code files for issue resolution, forming a crucial part of a retrieve-then-edit strategy.
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SWE-Fixer-Retriever-7B Overview
The internlm/SWE-Fixer-Retriever-7B is a specialized language model, fine-tuned from the Qwen2.5-7B architecture, developed by InternLM. It serves as a core component of the SWE-Fixer framework, which aims to resolve real-world GitHub issues through an efficient retrieve-then-edit pipeline. This model, with 7.6 billion parameters and a 131,072 token context length, is specifically engineered to act as a code file retriever.
Key Capabilities
- Code File Retrieval: Its primary function is to accurately identify and retrieve relevant code files pertinent to a given GitHub issue.
- Integration with SWE-Fixer: Designed to work seamlessly within the SWE-Fixer's two-component system, complementing the code editor.
- GitHub Issue Resolution: Contributes to a streamlined process for addressing and fixing software bugs and issues reported on GitHub.
Good For
- Developers and researchers working on automated software engineering tasks.
- Applications requiring intelligent retrieval of code context for bug fixing or code modification.
- Enhancing existing code repair or issue resolution pipelines with a dedicated retrieval component.
Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.