LocoreMind/LocoTrainer-4B
LocoreMind/LocoTrainer-4B is a 4-billion parameter MS-SWIFT domain expert agent, developed by LocoreMind, trained via knowledge distillation from Qwen3-Coder-Next. It uniquely combines multi-turn tool-calling with deep MS-SWIFT framework knowledge, enabling it to analyze codebases and generate comprehensive markdown reports without needing a separate reasoning model. With a 32,768-token context length, it excels at end-to-end code analysis and report generation specifically within the MS-SWIFT ecosystem.
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LocoTrainer-4B: MS-SWIFT Domain Expert Agent
LocoTrainer-4B, developed by LocoreMind, is a 4-billion parameter language model specifically designed as a domain expert agent for the MS-SWIFT framework. Unlike general-purpose code agents, this model is trained via knowledge distillation from Qwen3-Coder-Next, focusing on multi-turn tool-calling and deep understanding of MS-SWIFT.
Key Capabilities
- MS-SWIFT Domain Expertise: Accurately answers framework questions, trained on documentation, CLI parameters, and project structures.
- Tool-Calling Agent: Generates structured JSON for
Read,Grep,Glob,Bash, andWritetools to interact with codebases. - End-to-End Reports: Capable of generating complete, well-structured markdown analysis reports from a single query.
- Long Context: Supports a maximum sequence length of 32,768 tokens, covering a significant portion of long-context analysis scenarios.
- Local Deployment: A GGUF quantized version is available for efficient, zero API cost inference.
Good For
- Developers working with the MS-SWIFT framework who need an intelligent agent for codebase analysis.
- Automating the generation of detailed markdown reports on MS-SWIFT project structures and configurations.
- Scenarios requiring an agent that can perform multi-turn tool interactions (Read, Grep, Glob, Bash, Write) within a specific code domain.
- Users seeking a specialized, locally deployable code analysis tool with a substantial context window.
LocoTrainer-4B is designed to run within the LocoTrainer agent framework, which manages the full agent loop, including tool execution and report generation. While highly specialized for MS-SWIFT, its performance on unrelated codebases is untested, and complex multi-hop reasoning might benefit from larger models.