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

    kxsr_WAN14B_sidescroll_cinematic.safetensors LORA / Wan Video

    Model Information
    Model Name
    KXSR Side-Scroll Cinematic Concept WAN 14B + 1.3B T2V
    Version
    WAN 14B T2V
    Creator
    Kytra
    Size
    292.59 MB
    Downloads
    457
    Trigger
    kxsr
    Torrent Details
    BTIH
    3188AF14EC2BE9541EE9EDEFD2BC4D6231A3AFB2
    BTMH
    67010F5F52E6814D26CC268F2E7BAA6545D5EA234BFBE87F597A53D53B43F057
    SHA256
    9AB8630DEBE1B07EB7A168D2B8E43C393FC55EA2C833F1C0E4AD0CB459377D4C
    Upload Date
    about a year ago
    Uploader
    CivitasBay.org
    Status
    4 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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