ZIT I2I "Character LORA Transformation" Workflow
Use the pastebin workflow to transform any image into a character LORA style by downscaling to 768, generating a prompt with Qwen3VL, upscaling latents 2×, and applying SAM3 face fix with Inpaint Crop.
Implement the pastebin workflow in your own ZIT setup, adjust denoise to 0.5, and test with your own LORA models.
Summary
The author shares a step‑by‑step workflow that turns any input image into a new image styled with a character LORA, designed for the ZIT I2I model but adaptable to others. The process begins by downscaling the image to a 768‑pixel longer edge and feeding it to Qwen3VL, which generates a base prompt; the denoise value is tunable, with 0.45‑0.55 recommended. Next, the latent representation is upscaled 2×, improving detail before the LORA is applied again. Finally, a face‑fix pass uses SAM3 to detect faces and the Inpaint Crop node to refine them with the LORA, adding a touch of sharpness. A group bypasser node lets users toggle steps two and three, and the image is only saved after the final pass. The workflow also concatenates the LORA trigger word with the Qwen3VL prompt via a text‑concatenate node for flexible prompting.
Key changes
- Image downscaled to 768 and Qwen3VL generates a base prompt
- Denoise adjustable 0.45‑0.55 for optimal output
- Latent representation upscaled 2× before LORA application
- SAM3 detects faces and Inpaint Crop refines them with LORA
- Small sharpness added after face fix
- Group bypasser node toggles steps 2 and 3
- Image saved only after step 3
- Text concatenate node merges LORA trigger with Qwen3VL prompt