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    【LyCORIS / Illustrious-XL & NAI-XL】L3n4's Beholder Vision - 3o NAI-XL v-pred
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    Introduction to Beholder Vision

    Beholder Vision began as an experimental LyCORIS-LoCon for Illustrious-XL v0.1, trained on 126 meticulously curated images of aesthetic anime art.

    The concept: create “eye-candy” results, with flexibility to adapt to a variety of creative needs.

    Usage Recommendations

    Illustrious Ver. Parameters (Recommended as of Nov 30, 2024):

    • Strength: 1.01.2 (personally go for just 1.0)

    • Sampler: DPM++ 2M SDE (Karras)

    • Steps: 2535

    • CFG Scale: 67

    Changelog and Updates

    Dec 6, 2024
    Version 3o is here!

    Dec 4, 2024
    Version 2.1o is now available! This marks a complete rework of the initial test version for Pony. It has been trained for 5,490 steps, making it competitive with the original Beholder Vision.

    • Despite its extensive improvements, the new LoRA is just 54.8MB—half the size of previous Pony iterations of the model and vastly enhanced in every aspect.

    Dec 2, 2024

    The first version of Beholder Vision for FLUX.1 [dev], 1.3o, is now out.

    Nov 30, 2024
    I’m excited to announce Beholder Vision 1o (and its successor, 1.1o)!

    • 1o debuts as an experimental GLoRA, while 1.1o returns to classic LoCon, delivering improved performance at a smaller file size.

    • Now natively compatible with other SDXL models, including NoobAI-XL Epsilon-pred 1.0-Version.

    This version represents a significant leap forward over the 0.9beta, thanks to an upgraded training dataset and finely tuned parameters. (Details on the dataset and parameters will be shared if there’s interest.)

    Description

    FAQ

    LoCon
    SDXL 1.0
    by L3n4

    Details

    Downloads
    106
    Platform
    CivitAI
    Platform Status
    Available
    Created
    12/6/2024
    Updated
    4/22/2026
    Deleted
    -

    Files

    beholder_vision-3o.safetensors

    Mirrors

    Other Platforms (TensorArt, SeaArt, etc.) (1 mirrors)

    Available On (1 platform)

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