Finetuned 1.5B Qwen to generate bash commands at gpt-4o level using 400k synthetic examples + Fully opensource finetune dataset

Despite using LLMs for most of the coding, there was always one thing I kept Googling: Bash commands. It's quite flow-breaking to pause work, open Google, type the full query, go to Stack Overflow or similar, and look up the syntax I wanted. Intuitively, this always felt like something a small model would perform well at because you have a finite set of commands, well-defined syntax, and easy-to-generate training data. So one day I decided to actually find out. Over the course of the experiment, I tried six different models: SmolLM 135M, SmolLM 360M, Qwen3-0.6B, Qwen2.5-Coder-1.5B, Qwen3.5-0.8B, and Qwen3.5-2B.