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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):

    Since I couldn't "fix" the NaNs inside a LoRA, I decided to extract the soul of the best models. I managed to convert 6GB checkpoints into lightweight 500MB-1GB files.

    These allow you to inject the exact style/knowledge of a model into any other refined model without downloading the full base checkpoint 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).

    • Visual Only: Style extraction only (UNet).

    • 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.

    🟡 Architecture Warning (IL Base) Some of these files are based on the Illustrious (IL) architecture.

    • High Steps Warning: Since it's based on IL, using Duplo/Ultra on high-step merges might cause artifacts or corruption.

    • Recommendation: Use them at LOW STEPS (0.18-0.2) or stick to Total if you are merging deeply.

    • 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 😉


    Description

    Hi, today I wanted to see how checkpoint merge works. I like it, but the Minecraft concept needs more work. I'll upload two more versions tomorrow. I'm still testing how to steal information from checkpoints.