This workflow turns any animal prompt into a translucent, sugar-coated "sour gummy" character using the Qwen-Image model with a style LoRA. The core of the graph is a single Qwen-Image generation node (id: e5cfe5ba-2ae0-4bc4-869f-ab2228cb44d3) that handles text conditioning, sampling, and LoRA application, followed by a SaveImage node to write results to disk. Two annotations (Note and MarkdownNote) provide usage tips and a link to ComfyUI’s Subgraph guide so you can encapsulate and reuse the gummy-style block in your own projects.

Under the hood, the Qwen-Image node loads its VAE (qwen_image_vae.safetensors) and text encoder (Qwen 2.5 VL 7B), then injects the Gummy Animals LoRA into the model’s attention layers. This low‑rank adaptation steers the base model toward a consistent sour-candy aesthetic without retraining the full network. You control the look through the prompt (e.g., "a chubby corgi, translucent sour gummy, sugar crystals") and standard generation parameters like steps, guidance, resolution, seed, and the LoRA strength, allowing you to balance style intensity against subject fidelity. The SaveImage node captures final frames to your ComfyUI/output folder for quick iteration.