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Neural Repair & Portable Checkpoints Lora Type.

Hello! I'm back with something much juicier than ever!

Originally, I planned to release more Samplers (and I will), but I pivoted to solve a critical flaw I found in the community: Many popular merged checkpoints have a corrupted Layer 11.

• This translates to:

  • ❌ Text Encoder errors (NaNs).

  • ❌ Poor LoRA compatibility.

  • ❌ Massive information loss.

• And here's the solution: [Anti-Nans + RAM Cleaner] Uh-huh... The LoRA repair method failed, so I engineered a Runtime Fixer. Just paste the provided script into a new cell in your Colab/Notebook, run it before the WebUI, and you are good to go.

  • Herrscher Shield: Scans Layer 11 and eliminates NaNs in RAM instantly. No need to download fixed checkpoints.

  • AGGA Optimizer: Aggressively cleans RAM to prevent Colab crashes.

Okay, now let's talk about these Loras (Total / Duplo / Ultra):

These LoRAs function as "Structural Converters."

Think of them as a high-end "Cosplay" for your checkpoints: they allow a lightweight model to adopt the exact visual DNA, intelligence, and stylistic precision of a massive 6GB checkpoint (like Pony or Illustrious).

Instead of dealing with architectural instability or NaNs, I have distilled the core features of these giant models into optimized 500MB-1GB files. They let you inject the prompt-understanding and "soul" of a heavy base model into any other refined checkpoint without the overhead of downloading or loading 6GB files every time.

• In conclusion: Now you have a tool for every need:

  • Do you just want a refined DMD? -> Total.

  • Do you want the information and style? -> Duplo.

  • Do you want it all? It'll be a Copy -> Ultra.

🟢 TOTAL (Concept Injector):

• What it extracts?: Text Encoders + attn2 (Cross-Attention).

  • Complete Version: Extracts Text Encoders + attn2 (Cross-Attention). It’s the "Brain" of the model.

  • Visual Only Version: Extracts only the Style (UNet). | DMD2 Pure.

• What does it do?: Associates words with concepts.

  • Total knows that "Miku" means "Teal hair, long pigtails".

• Result: Corrects what is drawn, but the "brushstroke" remains from your base model.

🟡 DUPLO (Structure & Geometry):

• What it extracts?: Text Encoders + attn2 + attn1 (Self-Attention).

• What does it do?: Controls geometry and spatial composition. attn1 is where the "shape" of the style resides (eye size, body proportions, composition).

• Result: The image gets the structure of the source model (e.g., Pony), but the rendering (skin, lighting) is a hybrid.

  • Best for fixing anatomy while keeping your checkpoint's texture.

🔴 ULTRA (Full Replica):

• What it extracts?: EVERYTHING (attn, ff, proj, te).

• What does it do?: Copies the FeedForward (FF) layers too, which determine the Render Style (lighting, line weight, shading).

• Result: A complete conversion. The base model visually disappears and becomes a perfect replica of the source.

⚠️ IMPORTANT VERSIONS & WARNINGS

🟡 Visual Only vs. Complete (Zip)

• Visual (Online Gen Friendly): Use this for quick style transfer.

• Complete (Zip): Includes the "Fixed" files that connect text properly. Use this for serious work.

• Note: I fixed Duplo, but the IL & NoobAI base is sensitive. Treat it with care!

⚠️ Visual Only Usage Note: Don't be scared! Even though this is based on my DMD2 architecture:

It works perfectly at HIGH STEPS (20-30+) without burning (great for detailing).

It works perfectly at LOW STEPS (4-8) for speed.

Wink wink 😉

Thanks so much for your support! ♥