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    IDK aquatic nature background V2 - v2.0
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    # IDK Aquatic Nature Background V2

    ## About

    LoRA focused on the 'Aquatic Nature Background' concept for Illustrious-based SDXL models. It strengthens generation of underwater. Trained on a curated, normalized dataset with per-image loss curriculum.

    PT-BR: LoRA focada no conceito 'Aquatic Nature Background' para modelos SDXL baseados em Illustrious. Reforca a geracao de underwater. Treinada em dataset curado e normalizado com curriculo por loss por imagem.

    ## Trigger words

    ### Primary triggers

    ```

    underwater

    ```

    ### Supporting tags

    Frequent thematic tags from the training set - combine them with the primary triggers to steer the concept:

    ```

    bubble, air bubble, long hair, short hair, fish, blue eyes, barefoot, water, black hair, blue hair, twintails, nude, swimming, swimsuit

    ```

    ## Example prompts

    ```

    masterpiece, best quality, absurdres, beautiful woman standing in serene underwater coral reef, wearing flowing white dress, gentle sunlight rays, peaceful expression, <lora:IDK_aquatic-nature-background_V2:0.9>

    ```

    ```

    masterpiece, best quality, absurdres, beautiful woman floating in mystical bioluminescent ocean cave, completely nude with water droplets on skin, dramatic volumetric god rays, seductive gaze, <lora:IDK_aquatic-nature-background_V2:0.9>

    ```

    ## Preview generation settings

    | Setting | Value |

    | --- | --- |

    | Checkpoint | IDN_Illustrious_V10_T |

    | Size | 1280x720 + hires 1.5x RealESRGAN 4x+) = 1920x1080 |

    | Sampler | Euler a |

    | Steps | 28 (+14 hires) |

    | CFG scale | 5.5 |

    | Denoising strength | 0.4 |

    | Seeds | 1000-1009 |

    Negative prompt: worst quality, low quality, bad anatomy, bad hands, extra digits, fewer digits, missing fingers, jpeg artifacts, signature, watermark, username, blurry, lowres, bad proportions, deformed, mutated

    ## Recommended weight

    Use 0.8-1.1. This file is a V1+V2 merge (rank concatenation), which slightly dilutes each source - it tolerates and often benefits from weights a bit above 1.0.

    ## Training details

    - Base model: IDN_Illustrious_V10_T

    - Images: 61 (approved: 59)

    - Resolution: 512px

    - Network rank: 32 (alpha 32)

    - Loss threshold: 0.0523 (auto)

    - Passes: up to 10 (255 steps, stop: max_passes)

    - Method: curriculum requeue by per-image loss + dataset normalized to 262k px via RealESRGAN

    ## Changelog V2

    - New multi-source dataset (JoyTag captioning for photos, full captions).

    - Upscaled without cropping (dataset normalized via RealESRGAN).

    - Trained on IDN_Illustrious_V10_T with loss-based curriculum requeue.

    - Merged with the V1 LoRA (rank concatenation) to keep V1 behavior.

    File: IDK_aquatic-nature-background_V2.safetensors

    Description

    LORA
    Illustrious

    Details

    Downloads
    53
    Platform
    CivitAI
    Platform Status
    Available
    Created
    7/11/2026
    Updated
    7/12/2026
    Deleted
    -

    Files

    IDK_aquatic-nature-background_V2.safetensors