Files
StyleRef-styleref-comfyui/workflows/z-image/02-consistency-grid.json
T
BehzadandClaude Sonnet 5 70fcf9ef00 Demo a style whose effect is actually visible
The templates loaded a documentary photography style that compiles to
"photography, naturalistic lighting, deep focus, RAW-like" — close to what
SDXL produces unprompted — so the first queue looked like the nodes had done
nothing, and the demo subjects were unrelated scenery on top of that.

Load Renaissance Mythic Classicism instead: tempera-on-panel technique and a
muted Renaissance palette, unmistakable against a base render, with no
typography for the sampler to turn into gibberish and no subject it rules
out. Subjects are now concrete everyday scenes carrying no style words of
their own.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
2026-07-26 23:35:22 +02:00

1602 lines
26 KiB
JSON

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"Z-Image consistency grid \u2014 no account needed.\nOne style feeds three Apply nodes with three subjects; each renders through its own Z-Image sampler. Queue once and compare: one style, many subjects, a coherent set within this model.\n\nZ-Image Turbo (S3-DiT). Three model files download on first use: the UNET (diffusion_models/), the Qwen text encoder (text_encoders/), and the VAE (vae/).\nSampler defaults are turbo: 8 steps, CFG 1.0, euler/simple.\nZ-Image takes no negative prompt. The model runs without classifier-free guidance, so there is no negative encoder on this canvas \u2014 the sampler's negative input gets a zeroed conditioning. StyleRef still compiles the negative and previews it; put anything you need from it into `subject` on Apply as a positive phrase (\"fully clothed\", \"no text or watermark\"). Raising CFG does not bring the negative back.\nStyle prompts use the `diffusion` target \u2014 Z-Image reads the same tag-weighted output SDXL/SD1.5 use."
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