shootthesound

    shootthesound/Fizgig

    Fizgig — LoRA & Fine-tune Studio for Klein 9B, Krea 2, MiniMax H3, Qwen Image 2.1, Anima & Z-Image Turbo and Ace-Step XL: train, fine-tune, profile, repair and extract LoRAs & LoKR for Image, Video & Music Models

    ai
    deep-learning
    ace-step-1-5
    fine-tuning
    finetuning
    flux
    flux3
    Python
    Apache-2.0
    637 stars
    64 forks
    637 GitHub watchers
    Updated Oct 28, 2026
    View on GitHub

    Build with Backblaze B2

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    Where it stands

    Rank, growth pace and release cadence relative to everything GStars tracks.

    5 releases in the last 90 days, the latest today, with 14 contributors on GitHub.

    Use Cases & Benefits

    • Provides an end-to-end studio to train, fine-tune, profile, repair, and extract LoRAs and LoKRs for Klein 9B, Krea 2, MiniMax H3, and Qwen Image 2.1 models.
    • Enables full fine-tuning and advanced LoRA manipulation on consumer GPUs down to 8-16 GB, with unique tools for block-level repair, evolutionary exploration, and shareable visualizations.
    • Use for training and fine-tuning large AI models on mixed media datasets including photos, videos, and voice recordings on consumer-grade hardware.
    • Use for repairing and optimizing existing LoRAs block-by-block without retraining, improving model quality and style control efficiently.
    • Use for generating detailed profiling reports and evolutionary variations of LoRAs to discover optimal model configurations and shareable epoch morph visualizations.

    Should you depend on it?

    License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.

    License

    Apache 2.0

    Permissive: commercial use, modification and redistribution are allowed with attribution; includes an explicit patent grant from contributors.

    Community files

    • README: present
    • Contributing guide: present

    Watch-outs

    No watch-outs from GStars' checks.

    General guidance from repository metadata, not legal advice. How we score

    From the README

    Fine-tune base models on consumer GPUs — down to 16 GB. Fix broken LoRAs without retraining. Remix any LoRA into new variations in seconds.

    A train · fine-tune · repair · explore workbench built end-to-end for Flux 2 Klein 9B, Krea 2 and MiniMax H3 — training on photos, video, sound and voices, from quick LoRAs to the full base model.

    No GPU, or want a bigger one? Fizgig runs on rented hardware — one click, nothing to install.

    Deploying through that link supports Fizgig's development at no extra cost to you.

    Start-to-finish walkthrough — install, prep, caption, train, and the workbench tools

    Excerpt from the shootthesound/Fizgig README on GitHub (Apache-2.0 license). © its authors.Read the full README on GitHub

    Daily snapshots

    Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots

    Aug 31: +19

    +350 stars over 60 days across 6 snapshot days; best day +19 on Aug 31.

    Forks

    64+33

    Open issues

    8+1

    Compared with peers in AI

    Fastest-growing repositories GStars tracks in this cohort for the week of Nov 1, by 7-day star growth

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