Rebel Engine HORIZON - 3D

Rebel Engine HORIZON

CHECKPOINT
Original - TenStar Fund


Updated:

Rebel Engine HORIZON by Rebellion A.I. on Tensor.Art
Rebel Engine HORIZON by Rebellion A.I. on Tensor.Art
Rebel Engine HORIZON by Rebellion A.I. on Tensor.Art

HORIZON ARTIST V1.0 (12.5B)

Architecture: Asymmetric Dual-Rail DiT with Inter-Block Waveguide Routing (Krea-2 12.5B OPD Backbone) Training & Calibration Paradigm: Sequential Dyson-Relay Calibration & Subspace Molecular Autograd (AdamW)

Overview

Horizon Artist V1.0 is an advanced architectural re-wiring and synthetic subspace calibration of the 12-billion-parameter, 8-step On-Policy Distilled (OPD) Krea-2 foundation backbone. Rather than relying on conventional surface-level fine-tuning—which often degrades the fragile 8-step ODE denoising trajectory or introduces semantic concept bleeding—Horizon Artist V1.0 restructures the internal linear operators of the Diffusion Transformer into a 3-Tier Asymmetric Circuit connected by an Inter-Block Waveguide Bridge, while keeping the external tensor horizon (INT8 quantization & scales) 100% drop-in compatible with standard loaders.

Core Architectural Innovations:

  1. Three-Tier Functional Circuit Split (Zero-Hallucination Topology): Tier 1 — Hermetic Semantic Isolation (txtfusion @ 0.00% Drift): The Qwen3-VL text-fusion bridge is completely isolated from visual weight perturbations. The model retains 100% pure linguistic comprehension, capable of following 300+ word novel-length prompts, complex multi-panel layouts, and rendering razor-sharp typography without unwanted artifacts or concept bleeding. Tier 2 — Cayley–Lorentz Attention Deflectors (wq / wk @ ~2.16% RMS): Spatial addressing layers are calibrated using energy-preserving 2D Cayley–Lorentz plane rotations and symmetric polar retraction, acting as magnetic lenses that route incoming activations without distorting anatomical geometry. Tier 3 — Impedance-Matched Visual Synthesizers (wv / wo / mlp.up / mlp.down @ ~13.21% RMS): High-frequency visual synthesis, material physics, subsurface scattering, and brushwork dynamics are concentrated directly into the feature-writing layers using Kirchhoff impedance matching.

  2. OPD-Safe "Dual-Rail" Subspace Folding (W⊥​⊕W∥​): Over 3,584 primary denoising channels (W⊥​) per layer remain mathematically untouched, preserving the ultra-fast 8-step OPD convergence and deep obsidian blacks. Within the orthogonal 512-channel knowledge subspace (Qa​QaT​), the backbone’s native "sterile smoothing" (Coulomb screening) is selectively relaxed via quantum-tunneling compression curves, channeling harvested free energy directly into micro-textures (skin pores, wet silk tension, dispersion caustics, and crisp 2D ink linework).

  3. Sequential Dyson-Relay Calibration & Molecular Autograd (AdamW): Multi-domain visual capabilities were synthesized sequentially using Activation-Aware Probe Wavepackets (Xprobe​). Each calibration stage measures the existing circuit response (Ydone​) and injects only the missing residual action and orthogonal novelty—eliminating contrast overbaking even under extreme multi-style prompts. Inside each visual subspace, open-gradient PyTorch Autograd (AdamW) optimizes a skew-symmetric/symmetric Molecular Coupling Matrix (Mmol​), enabling the model to effortlessly render pure 8K macro photorealism, 1990s 2D cel-shaded anime, or surreal 2D/3D hybrid scenes within the same frame.

  4. Inter-Block Waveguide Bridge (Block 0→27 Relay): To prevent deep-layer signal attenuation, the output wavefronts (Ubridge​) emitted by Block k’s stream writers (attn.wo, mlp.down) into the Residual Highway are topologically coupled to the input tunnel gates of Block k+1 (wq, wk, wv, mlp.up), forming a continuous 28-block waveguide for high-frequency detail retention.

Version Detail

SDXL 1.0
11500
30

Project Permissions

Reprinting is strictly prohibited

    Use Permissions

  • Use in TENSOR Online

  • As a online training base model on TENSOR

  • Use without crediting me

  • Share merges of this model

  • Use different permissions on merges

    Commercial Use

  • Sell generated contents

  • Use on generation services

  • Sell this model or merges

Related Posts