fofr/juggernaut-xl-lightning:c9a24c32 – Run with an API on Replicate

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fofr /juggernaut-xl-lightning:c9a24c32

Input

prompt

string

Shift + Return to add a new line

A portrait photo, neon red hair, lightning stormA portrait photo, neon red hair, lightning storm

Default: ""

negative_prompt

string

Shift + Return to add a new line

Things you do not want to see in your image

Default: ""

number_of_images

integer

(minimum: 1, maximum: 10)

Number of images to generate

Default: 1

width

integer

Default: 1024

height

integer

Default: 1024

output_format

string

Format of the output images

Default: "webp"

output_quality

integer

(minimum: 0, maximum: 100)

Quality of the output images, from 0 to 100. 100 is best quality, 0 is lowest quality.

Default: 80

seed

integer

Set a seed for reproducibility. Random by default.

disable_safety_checker

boolean

Disable safety checker for generated images.

Default: false

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

npx create-replicate --model=fofr/juggernaut-xl-lightning

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";

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

Run fofr/juggernaut-xl-lightning using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "fofr/juggernaut-xl-lightning:c9a24c321ceb0b7843b872dcae82109dddadd1f82e94b115ee39289e0e182e40",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "A portrait photo, neon red hair, lightning storm",
      output_format: "webp",
      output_quality: 80,
      negative_prompt: "",
      number_of_images: 1
    }
  }
);
console.log(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 fofr/juggernaut-xl-lightning using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "fofr/juggernaut-xl-lightning:c9a24c321ceb0b7843b872dcae82109dddadd1f82e94b115ee39289e0e182e40",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "A portrait photo, neon red hair, lightning storm",
        "output_format": "webp",
        "output_quality": 80,
        "negative_prompt": "",
        "number_of_images": 1
    }
)
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 fofr/juggernaut-xl-lightning 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": "c9a24c321ceb0b7843b872dcae82109dddadd1f82e94b115ee39289e0e182e40",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "A portrait photo, neon red hair, lightning storm",
      "output_format": "webp",
      "output_quality": 80,
      "negative_prompt": "",
      "number_of_images": 1
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

3.4 seconds

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