chimbiwide/Qwen3-Go
Qwen3-Go is a 4 billion parameter experimental model developed by chimbiwide, fine-tuned specifically for Go code completion. Utilizing the Go-Code-Large dataset, this model is optimized for generating Go programming language code. It offers specialized capabilities for developers working with Go, distinguishing it from general-purpose language models.
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Qwen3-Go: Specialized Go Code Completion Model
Qwen3-Go is an experimental 4 billion parameter model developed by chimbiwide, specifically fine-tuned for Go programming language code completion. This model leverages the Go-Code-Large dataset to enhance its proficiency in generating Go code.
Key Capabilities
- Go Code Completion: Optimized for generating syntactically correct and contextually relevant Go code snippets.
- Experimental Focus: Developed as a local fine-tuning experiment, demonstrating the potential for specialized code generation on consumer-grade hardware.
Training Details
The model was trained locally on a 5070Ti GPU using Unsloth, with 4-bit loading. The training process involved a batch size of 8 for 1 epoch, completing in approximately 19 hours.
Good For
- Developers seeking a specialized model for Go language code assistance.
- Experimentation with fine-tuned models for specific programming tasks.
- Use cases requiring efficient Go code generation.