Asystemoffields/Cclilqwen
Cclilqwen is a 0.6 billion parameter Qwen3-based model developed by Asystemoffields, fine-tuned for a unique blend of creative writing, code generation, and agentic tool use, while maintaining strong mathematical reasoning. It was created by merging four specialist LoRA fine-tunes using manual DARE-TIES. This model excels in specific tasks like Python coding and tool calling with a 100% success rate, offering a versatile solution for applications requiring diverse capabilities within a compact footprint.
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Cclilqwen: A Specialized 0.6B Model for Creative, Code, and Agentic Tasks
Cclilqwen is a compact yet powerful 0.6 billion parameter model built upon the Qwen3-0.6B base, developed by Asystemoffields. It stands out due to its unique training methodology, which involved fine-tuning four specialist models (for math self-play, creative writing, Python coding, and tool use) and then merging them using a manual DARE-TIES approach. This process resulted in a highly capable model optimized for a diverse set of tasks.
Key Capabilities
- Enhanced Math Reasoning: Achieves 48.5% on GSM8K, nearly doubling the base Qwen3-0.6B's performance.
- Robust Tool Calling: Demonstrates a 100% success rate in generating valid JSON and correct
<tool_call>tags for agentic workflows. - Proficient Code Generation: Successfully generates correct Python solutions for common programming problems like palindrome, fibonacci, and stack implementations.
- Versatile Creative Writing: Capable of producing vivid prose, including gothic horror and dark humor, with effective perspective shifts.
Good for
- Applications requiring a small, efficient model with strong multi-modal capabilities.
- Developers needing reliable tool-calling functionality for agentic systems.
- Generating creative text or code snippets where a compact model is preferred.
- Use cases where a balance of mathematical reasoning, coding, and creative output is essential, despite the parameter size.