CivArchive
    I2P33: Blink P!ss LoRA - low
    Preview 1


    Join my discord for access to Version 5: https://discord.gg/8wMr2mmaRF

    Follow me on HuggingFace for all of my other releases that I cannot post here:

    https://huggingface.co/obsxrver/

    Update: I2-4 Public Release

    I2-4 is the best freely available blink LoRA today. You can download and run it for free now.

    No GPU? No Problem

    Run ComfyUI on a cloud GPU using Vast.AI with this template https://cloud.vast.ai/?ref_id=208628&creator_id=208628&name=ComfyUI%20-%20Wan%202.2%20LoRA%20demo

    WORKFLOW:

    Download the workflow file https://huggingface.co/obsxrver/wan2.2-i2v-/resolve/main/config.json?download=true and drag into ComfyUI.

    SageAttention:

    The Vast.AI
    template already provisions the instance, downloading all necessary
    LoRA Files and installing SageAttention. However, if running locally,
    you will need to install SageAttention to run the workflow:

    ``` pip install sageattention ```

    Technical Explanation

    Blink
    introduces a novel training methodology for Image-to-Video (I2V)
    diffusion transformers, termed Identity Invariant Action Mapping (IIAM).
    This technique addresses the persistent challenge of identity drift and
    hallucination in generative video by decoupling subject identity from
    temporal action dynamics.

    Traditional I2V training often results
    in the model creating a smooth, continuous video, Blink teaches the
    model to perform a hard-cut transition, switching to a completely new
    scene, while preserving the and identity characteristics of the
    input image. We achieve this by utilizing a specific data preprocessing
    strategy:

    1. Temporal Splicing: Training data consists of a 0.3-second static frame (the "before" image of the subject. Derived from the video using Qwen-Image-Edit) prepended to a 4.7-second action sequence
    (the "after". Whatever you are training the LoRA to do). This "jumpcut"
    forces the model to attend to the initial static latents as the ground
    truth for identity.

    2. Identity-Agnostic & Discontinuity-Forcing Captioning:


    Template: "a [man|woman], jumpcut, after the transition, [he|she] is
    (any change in appearance), [he|she] is (the action happening in the
    "after" sequence)"

    By any uniquely identifying
    descriptors (e.g., hair color, structure, clothing), using only
    generic identity references ("man", "woman", "he", "she"), the model is
    forced to map the learned motion vectors and physics simulations
    directly onto the visual topology provided in the initial frame. The
    model learns to bind the discontinuous transition - the "blink" - to the
    "jumpcut, after the transition" tokens.

    Future Applications:

    The
    IIAM/Blink framework is content-agnostic and can be applied to any set
    of action clips to create modular, "plug-and-play" motion LoRAs for
    generative video workflows.


    Description


    FAQ







    Comments (7)

    boobkake222026년 5월 14일· 19 reactionsCivitAI


    Here before the delete.

    UrdNine2026년 5월 14일CivitAI


    Finally!!!!!!!!!!!!!!!!

    fronyax2026년 5월 14일CivitAI


    This and the latest from igoon's are superb

    Keroro_Gunso2026년 5월 14일· 1 reaction


    Where to find

    Jellai2026년 5월 14일


    Latest? I just see stuff that's at least 3 months old on huggingface. Is that what you mean?

    fronyax2026년 5월 14일


    @Jellai
    I subbed to him. Choking is the latest one, it was released a
    couple of days ago. 3 months? He released a lot since then.

    crafted1012026년 5월 14일


    @fronyax link ?




    Description

    LORA
    Wan Video

    Details

    Downloads
    2
    Platform
    SeaArt
    Platform Status
    Available
    Created
    5/14/2026
    Updated
    5/14/2026
    Deleted
    -
    Trigger Words:
    jumpcut
    after the transition

    Files

    Available On (2 platforms)

    Same model published on other platforms. May have additional downloads or version variants.