@huggingface/tasks/dist/commonjs/tasks/image-text-to-video/data.js

List of ML tasks for huggingface.co/tasks

"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
const taskData = {
    datasets: [],
    demo: {
        inputs: [
            {
                filename: "image-text-to-video-input.jpg",
                type: "img",
            },
            {
                label: "Input",
                content: "Darth Vader is surfing on the waves.",
                type: "text",
            },
        ],
        outputs: [
            {
                filename: "image-text-to-video-output.gif",
                type: "img",
            },
        ],
    },
    metrics: [
        {
            description: "Frechet Video Distance uses a model that captures coherence for changes in frames and the quality of each frame. A smaller score indicates better video generation.",
            id: "fvd",
        },
        {
            description: "CLIPSIM measures similarity between video frames and text using an image-text similarity model. A higher score indicates better video generation.",
            id: "clipsim",
        },
    ],
    models: [
        {
            description: "A powerful model for image-text-to-video generation.",
            id: "Lightricks/LTX-Video",
        },
    ],
    spaces: [
        {
            description: "An application for image-text-to-video generation.",
            id: "Lightricks/ltx-video-distilled",
        },
    ],
    summary: "Image-text-to-video models take an reference image and a text instructions as and generate a video based on them. These models are useful for animating still images, creating dynamic content from static references, and generating videos with specific motion or transformation guidance.",
    widgetModels: ["Lightricks/LTX-Video"],
    youtubeId: undefined,
};
exports.default = taskData;