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    Focused mainly on realistic portraits and flexibility, with higher native resolution support. (V8: 896x1152, up to 1024x1280, 1280x1280)

    Example images are somewhat cherry-picked, no hi-res upscale used, no face-fix.

    CLIP Skip 2 might help with realism in some cases while sacrificing fantasy aspects, experiment with it.

    V9/V8/V7 comparison (896x1152):

    V8/V7 comparisons:

    1024x1280

    768x1024

    V1 Recipe (might not be exactly how I did it):

    Exp1-Tier1: (using add difference for all)

    • GreyModel v12.0.0 + Dreamlike Photo v2 (25%)

    • + Woop Photo (25%)

    • + Protogen Infinity (25%)

    • + ArtEros (15%)

    • + HSPU (15%)

    • + URPM (15%)

    • + F222 (15%)

    • + AlmostDirty (15%)

    • + BondageV10 (5%)

    • + TWAM (5%)

    • + SXD1.0 (5%)

    • + 3DKX1.1 (1%)

    • + Hassan1.5 (1%)

    • + OpenJourneyV2 (1%)

    • + StrangeDedication2 (1%)

    Exp1-Tier2-Part1: (still add diff)

    • GreyModel12.0.0 + AnalogPhoto (25%)

    • + Dreamlike Photoreal v1 (25%)

    • + Amphibia Diffusion (15%)

    • + Artstation (15%)

    • + CALARTS (15%)

    • + ChromaV5 (15%)

    • + Corporate Memphis (15%)

    • + NitroDiffusion (10%)

    • + Dreamlike Diffusion (10%)

    • + FracTime (10%)

    • + InkPunk (10%)

    • + Midjourney-v4-diff (10%)

    • + RPGv2 (10%)

    • + SeekArt MEGA (10%)

    • + Colorjizz768 (5%)

    • + Double Exposure (5%)

    • + MegaPals (5%)

    Exp1-Tier2-Part2: (add diff)

    • GreyModel12.0.0 + MosaicArt (5%)

    • + RealisticCartoon (5%)

    • + Strahd (5%)

    • + Technicolor (5%)

    • + DMT Entity (1%)

    • + Elysium (1%)

    • + BalloonArt (1%)

    • + DnDClasses (1%)

    • + DarkVictorian (1%)

    • + ComicDiffusion V2 (1%)

    • + DiscoDiffusion (1%)

    • + Dvmjv4 (1%)

    • + Halloween (1%)

    • + Lichtspiel (1%)

    • + Lnkdn (1%)

    • + Midjrny-v4 (1%)

    • + Mtg-style (1%)

    • + NekoMix (1%)

    • + Nekrofaerie (1%)

    • + SDHeroCalm (1%)

    • + SpiderVerse (1%)

    • + Ssmoky (1%)

    • + SynthwaveV2 (1%)

    • + TDST (1%)

    • + VanGogh (1%)

    • + Vectorartz (1%)

    • + Voxelish (1%)

    • + Wa-vy (1%)

    • + Woolitize768 (1%)

    Exp1-Tier3 (add diff):

    • GreyModel12.0.0 + Babetopia (20%)

    • + Instababe (20%)

    • + PovSkinDream (15%)

    • + PowerfulMix20 (15%)

    • + GTMult v1? (15%)

    • + LatexRaw (10%)

    • + ClassicNegative (10%)

    • + Furrystaber (5%)

    Exp1-Tier4 (add diff):

    • GreyModel12.0.0 + RealismMix (20%)

    • + Hassan1.4 (15%)

    • + AttractiveMix (10%)

    • + VoluptuousMix (10%)

    • + SamDoesBimboes (1%)

    The Tiers separately are UNUSABLE because of all the AddDiffs, but merging them together brings them back to usable territory.

    Probably merged these with Weighted sum as

    ( (Tier1 + Tier2Part1)*0.5 + (Tier2-Part2 + Tier3)*0.5 ) + Tier4 * ?

    Then merged it with a custom DB model (trained on a face, but it also learned a bit of analog photo style) to tone it down a bit

    = Exp1Final

    Exp2 (using weighted sum):

    • ArtEros + RealVision1.2 (50%)

    • Grey12.0.2 + ProjectPhoto BETA (50%)

    • SexyRealism + TheGirlNextDoor (50%)

    • Deliberate1.1 + AnythingFurry (25%)

    • Visigen + Futagen (25%)

    • ArtRealV + GreyProjectPB (50%)

    • DelibAnyFur + VisiFuta (50%)

    • DelibAnyVisiFuta + SexyRGirlND (35%)

    • ArtRealGreyPro + DelibAnyVisiFutaSexyRGirlND (35%)

    • + Emotional Puppeteer (1%)

    = Exp2Final

    Exp1Final + Exp2Final weighted sum 50%?

    = Exp3

    Moving it back a bit towards photorealism:

    Exp3+ (not sure about the weights from here on, but used weighted sum)

    • (Analog + SimpMaker3k1 + DoubleExp + Attractive + Licthspiel)

    • + (SexyRealism + TheGirlNextDoor)

    • + (RealVision1.2 + ProjectPhotoBeta)

    • + (Dreamlike PhotoV2 + Deliberate1.1)

    = WyvernMix V1

    Description

    applied training to a custom merge of XL models, trying to improve portraits.

    The mix contains ChimeraMiXL as well, also the LUT training, so inherits those keywords.

    FAQ

    Comments (6)

    HitManLeeAug 7, 2023· 1 reaction
    CivitAI

    Quite remarkable work, so far it seems to be a big step forward relative to other authors' model fine-tuning, with amazingly improved results, may I ask how you trained?

    wier
    Author
    Aug 7, 2023· 3 reactions

    thank you, glad you like it!

    nothing fancy, just picking different subsets (300-2000 images) of my accumulated dataset, training LoRAs on them, so I can test them at different epochs and strengths, then merge them into the current WIP checkpoint as they fit best, and fix some minor issues with MBW merging. then test and repeat

    HitManLeeAug 8, 2023

    @wier Thank you for your answer!

    morbutoAug 10, 2023· 1 reaction

    @wier Nice, that's roughly the same way I'm training SDXL too, seems to be the best method so far 😁

    BinaryBottleBakeAug 8, 2023· 1 reaction
    CivitAI

    Does this model require the refiner?

    wier
    Author
    Aug 9, 2023· 3 reactions

    the example pics were generated without it, but sometimes I get slightly better results with the refiner turned on, around 30-40 steps with 10% refining, but couldn't really get the hang of it in A1111 yet.

    you can try generating the same image with the same seed with and without refiner and check how much difference there is

    eg. 20 steps, no refiner: https://ibb.co/THX2bZm
    50 steps, 10% refiner: https://ibb.co/yfx6w7j

    Checkpoint
    SDXL 1.0
    by wier

    Details

    Downloads
    760
    Platform
    CivitAI
    Platform Status
    Available
    Created
    8/6/2023
    Updated
    5/13/2026
    Deleted
    -

    Files

    wyvernmix15XL_xlV1.safetensors

    Mirrors

    HuggingFace (1 mirrors)

    Available On (1 platform)

    Same model published on other platforms. May have additional downloads or version variants.