KXSR Side-Scroll Cinematic Concept WAN 14B + 1.3B T2V

    kxsr_WAN1-3B_sidescroll_cinematic.safetensors LORA / Wan Video

    Model Information
    Model Name
    KXSR Side-Scroll Cinematic Concept WAN 14B + 1.3B T2V
    Version
    WAN 1.3B T2V
    Creator
    Kytra
    Size
    166.95 MB
    Downloads
    452
    Trigger
    kxsr
    Torrent Details
    BTIH
    EEAF2CB03E1166C33A0CE8834B44800FD46431DA
    BTMH
    5592B71023E678F8B5C9DA3A9A3F426E6CB03097E255F1D849C57FAFD96E1F2E
    SHA256
    DEBEAEE71B2EC135D3C19016E8DF69CD8E9093B6870EE2D3078831CCACA78495
    Upload Date
    about a year ago
    Uploader
    CivitasBay.org
    Status
    5 Seeders
    0 Peers
    Info

    KXSR Side-Scroll Cinematic LorA for WAN 2.1 14B and 1.3B T2V

    In collaboration with @machinedelusions [https://civarchive.com/user/machinedelusions]

    KXSR
    Labs presents:
    This LoRA enables the creation of cinematic sequences featuring characters and imaginative scenery with fast-paced high-octane scrolling action. The typical view will be from a side-scroll perspective with dynamic movement in horizontal aspect ratio generation. Can still create fun results at other aspect ratios/resolutions.

    Use the trigger word "kxsr" to activate the model's specialized training.

    Prompt Format

    kxsr, [describe the person/thing] [ACTION-VERB HERE: sprints/runs/jumps/hurdles/hustles/etc] [describe the scenery/environment of the world and other actions happening around them]
    

    Example Prompt

    kxsr, A prototype mech sprints across testing grounds, hydraulic legs pumping as its pilot navigates through obstacles, warning lights reflecting off titanium plating. It hurdles barriers and slides beneath suspended containers with precision. Outside the complex, an alien battlefield extends where orbital cannons fire from distant mountains and enemy forces advance through smoke-filled terrain.
    
    • CFG: 5.5

    • Shift value: 4.0

    • LoRA strength: 1.0

    • ~73 frames

    • 720x1280 horizontal aspect ratio

    Technical Details

    • Base model: WAN 2.1 14B and 1.3B Text2Video

    • Training dataset: 115 clips

    • Resolution: 1280 x 720 (horizontal format)

    • Frame count: 73 frames per clip

    • For optimal results, maintain these specifications during inference

    This LoRA works best when you provide detailed descriptions of both the subject and the surrounding environment while following the prescribed format.

    Screenshot shows my typical inference testing setup for lora evals:

    Gallery
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