18-Video
Last updated
Last updated
The most basic way of using the image to video model is by giving it an init image like in the following workflow that uses the 14 frame model. You can download this webp animated image and load it or drag it on to get the workflow.
You can also use them like in this workflow that uses SDXL to generate an initial image that is then passed to the 25 frame model:
video_frames: The number of video frames to generate.
motion_bucket_id: The higher the number the more motion will be in the video.
fps: The higher the fps the less choppy the video will be.
augmentation level: The amount of noise added to the init image, the higher it is the less the video will look like the init image. Increase it for more motion.
VideoLinearCFGGuidance: This node improves sampling for these video models a bit, what it does is linearly scale the cfg across the different frames. In the above example the first frame will be cfg 1.0 (the min_cfg in the node) the middle frame 1.75 and the last frame 2.5. (the cfg set in the sampler). This way frames further away from the init frame get a gradually higher cfg.
If you want the exact input image you can find it on the
