ali-vilab/i2vgen-xl:5821a338 | Run with an API on Replicate

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ali-vilab /i2vgen-xl:5821a338

Playground API

Input

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

npx create-replicate --model=ali-vilab/i2vgen-xl

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 ali-vilab/i2vgen-xl using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "ali-vilab/i2vgen-xl:5821a338d00033abaaba89080a17eb8783d9a17ed710a6b4246a18e0900ccad4",
  {
    input: {
      image: "https://replicate.delivery/pbxt/KAaakS0H8XnzXtfFCWvqUBjC759vUXdJ18Y5JgfeGFA2PTie/img_0004.png",
      prompt: "A girl with yellow hair and black clothes stood in front of the camera",
      max_frames: 16,
      guidance_scale: 9,
      num_inference_steps: 50
    }
  }
);

// 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.

Install Replicate’s Python client library:

pip 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 the client:

import replicate

Run ali-vilab/i2vgen-xl using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "ali-vilab/i2vgen-xl:5821a338d00033abaaba89080a17eb8783d9a17ed710a6b4246a18e0900ccad4",
    input={
        "image": "https://replicate.delivery/pbxt/KAaakS0H8XnzXtfFCWvqUBjC759vUXdJ18Y5JgfeGFA2PTie/img_0004.png",
        "prompt": "A girl with yellow hair and black clothes stood in front of the camera",
        "max_frames": 16,
        "guidance_scale": 9,
        "num_inference_steps": 50
    }
)
print(output)

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

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Run ali-vilab/i2vgen-xl using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "ali-vilab/i2vgen-xl:5821a338d00033abaaba89080a17eb8783d9a17ed710a6b4246a18e0900ccad4",
    "input": {
      "image": "https://replicate.delivery/pbxt/KAaakS0H8XnzXtfFCWvqUBjC759vUXdJ18Y5JgfeGFA2PTie/img_0004.png",
      "prompt": "A girl with yellow hair and black clothes stood in front of the camera",
      "max_frames": 16,
      "guidance_scale": 9,
      "num_inference_steps": 50
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

Output

Generated in

1 minute 56 seconds

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