README.md

metadata

title: Zeta-Chroma Test Bench
emoji: 🎨
colorFrom: purple
colorTo: indigo
sdk: gradio
sdk_version: 5.33.0
app_file: app.py
pinned: false
hardware: zero-a10g
tags:
  - ml-intern

🎨 Zeta-Chroma Test Bench

Generates images from lodestones/Zeta-Chroma — a pixel-space diffusion model based on the Z-Image architecture.

This Space runs a custom inference pipeline re-implemented from the ComfyUI source code, since this model variant is not yet supported by the diffusers library.

How it works

• Model: NextDiTPixelSpace — 6.5B parameter pixel-space diffusion transformer with dec_net decoder
• Text encoder: Qwen3 4B (layer -2, chat template) from Tongyi-MAI/Z-Image
• Scheduler: Custom Euler sampler with AuraFlow shift=8.0 and beta sigmas (α=0.6, β=0.6)
• No VAE — model generates RGB pixels directly (patch_size=32)
• Free — runs on ZeroGPU, uses the visitor's own daily GPU quota

Features

• 🧪 Test Suite — 4 challenging furry art prompts (hyper-realism → toony) with fixed seeds for cross-version comparison
• 🎨 Custom Prompt — full control over prompt, negative prompt, resolution, steps, CFG, shift, and seed
• 🔖 Checkpoint tracking — displays the model's commit SHA so you know which training checkpoint is active
• 📡 Webhook — auto-triggers on model updates (configure at webhook settings)

Resolution presets

All resolutions are multiples of the model's patch_size=32:

Ratio	Landscape	Portrait
1:1	512², 768², 1024²	—
4:3	1024×768	768×1024
16:9	1024×576	576×1024
5:3	1280×768	768×1280
5:4	1280×1024	1024×1280

Privacy

All generations are private to your browser session. No images are stored server-side or shared between users. GPU time is billed to your account quota, not the Space owner's.

⚠️ WIP Model

This is a work-in-progress training checkpoint. Image quality and prompt adherence will improve as training progresses. The webhook will automatically pick up new checkpoint versions.