ctrl+k

jichengdu/wan-i2v

i2v-14B-720p-2.1

Public
316 runs
Run with an API
Pricing
GitHub
License
Weights
Playground API Examples README Versions

Input

Run this model in Node.js with one line of code:

npx create-replicate --model=jichengdu/wan-i2v
or set up a project from scratch
Install Replicate’s Node.js client library:
npm install replicate
Set the REPLICATE_API_TOKEN environment variable:
export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import and set up the client:
import Replicate from "replicate";
import fs from "node:fs";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run jichengdu/wan-i2v using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "jichengdu/wan-i2v:d6a220d6990c8e166d4639a7b8fc9ef744e8e5297af2aef18edde1477140782e",
  {
    input: {
      image: "https://replicate.delivery/pbxt/MfpzR98ZJmwZM7oUcVqeFNW5DUvtTGFDTopDvFC40JdGhZKB/i2v_input.JPG",
      prompt: "Summer beach vacation style, a white cat wearing sunglasses sits on a surfboard. The fluffy-furred feline gazes directly at the camera with a relaxed expression. Blurred beach scenery forms the background featuring crystal-clear waters, distant green hills, and a blue sky dotted with white clouds. The cat assumes a naturally relaxed posture, as if savoring the sea breeze and warm sunlight. A close-up shot highlights the feline's intricate details and the refreshing atmosphere of the seaside.",
      max_area: "1280*720",
      num_frames: 81,
      sample_shift: 5,
      sample_steps: 30,
      frames_per_second: 16,
      sample_guide_scale: 5
    }
  }
);

// To access the file URL:
console.log(output.url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", output);

To learn more, take a look at the guide on getting started with Node.js.

Sign in to run this model:

Sign in with GitHub

By signing in, you agree to our
terms of service and privacy policy

Output

Generated in
Tweak itIterate in playgroundShareReportView full prediction

Examples

View more

Run time and cost

This model runs on Nvidia A100 (80GB) GPU hardware. We don't yet have enough runs of this model to provide performance information.

Readme

Wan: Open and Advanced Large-Scale Video Generative Models

In this repository, we present Wan2.1, a comprehensive and open suite of video foundation models that pushes the boundaries of video generation. Wan2.1 offers these key features:

👍 SOTA Performance: Wan2.1 consistently outperforms existing open-source models and state-of-the-art commercial solutions across multiple benchmarks. 👍 Supports Consumer-grade GPUs: The T2V-1.3B model requires only 8.19 GB VRAM, making it compatible with almost all consumer-grade GPUs. It can generate a 5-second 480P video on an RTX 4090 in about 4 minutes (without optimization techniques like quantization). Its performance is even comparable to some closed-source models. 👍 Multiple Tasks: Wan2.1 excels in Text-to-Video, Image-to-Video, Video Editing, Text-to-Image, and Video-to-Audio, advancing the field of video generation. 👍 Visual Text Generation: Wan2.1 is the first video model capable of generating both Chinese and English text, featuring robust text generation that enhances its practical applications. 👍 Powerful Video VAE: Wan-VAE delivers exceptional efficiency and performance, encoding and decoding 1080P videos of any length while preserving temporal information, making it an ideal foundation for video and image generation.