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    [Illustrious] Cutting T-shirt Challenge - v0.1 Test Illustrious
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    [Illustrious] Cutting T-shirt Challenge

    Description

    • Challenge that viral in X/Twitter

    • Work in progress LoRA (maybe some edit dataset to produce better LoRA)

    trigger word

    cutting_challenge, like and retweet, number, white shirt

    Limitations

    • Number of favorite and retweet is not accourate

    • Text stills not good

    Training Details

    LoRA rank

    • LoRA standard

    dataset

    • 72 images

    parameters

    • resolution = 1024

    • batch size = 2

    • network dim,alpha = 12,12

    • mix/save precision = bf16/bf16

    • optmizer = Lion (weight_decay=0.05)

    • UNet LR = 3e-5

    • TE LR = 1e-5

    • scheduler = cosine_with_restarts (3 restarts)

    • l2 loss

    • alpha_mask

    steps

    • epochs = 10

    • total steps = 3600

    • repeat = 10

    tools

    • kohya-ss GUI v24.3.0 FORKED by vjumpkung

    • torch 2.5.0 cu124

    • Runpod RTX 4090

    avg weight

    • UNet average weights : 0.009967144748026674

    • TE1 average weights : 0.007946787285618484

    • TE2 average weights : 0.006517791320220567

    *This LoRA is for studying LoRA training with new technique so do not use for challenge in X/Twitter.

    *If you see my model reposted on other image generation service please report to me.

    Description

    test version with remove background dataset

    FAQ

    Comments (2)

    azki_is_very_cuteMar 11, 2025
    CivitAI

    someone is reposted this model in pixai, link is this; https://pixai.art/model/1850132219886529630?utm_source=copy_web

    vjumpkung
    Author
    Mar 11, 2025

    Thank you for tell me to claim my model back to me.

    LORA
    Illustrious

    Details

    Downloads
    568
    Platform
    CivitAI
    Platform Status
    Available
    Created
    2/21/2025
    Updated
    6/18/2026
    Deleted
    -
    Trigger Words:
    cutting_challenge, like and retweet, number, white shirt

    Files

    cutting_challenge_illustrious_v1.safetensors