Qwen3.5 fine-tune drops for SD prompt generation

The use of an LLM-in-the-loop to iteratively refine prompts against target images is a clever approach to building specialized datasets.

• –The pipeline uses multiple rounds of LLM comparison between a target and generated image to tailor the prompt to a specific SD model
• –Relying entirely on synthetic data sidesteps traditional dataset curation bottlenecks and raises interesting questions about copyright
• –The 4-billion parameter size makes it highly accessible for local deployment alongside existing Stable Diffusion workflows