replicategithubwc/juggernaut-sdxl – Run with an API on Replicate

replicategithubwc / juggernaut-sdxl

Cold

Public
26.1K runs
A100 (80GB)

Run with an API

Playground API Examples README Versions

Input

prompt

string

Shift + Return to add a new line

a photo of an astronaut riding a horse on marsa photo of an astronaut riding a horse on mars

Input prompt

Default: "a photo of an astronaut riding a horse on mars"

negative_prompt

string

Shift + Return to add a new line

Specify things to not see in the output

image_prompt

file

Input image prompt for image_prompt mode

image

file

Input image for img2img or inpaint mode

mask

file

Input mask for inpaint mode. Black areas will be preserved, white areas will be inpainted.

width

integer

Width of output image

Default: 768

height

integer

Height of output image

Default: 768

num_outputs

integer

(minimum: 1, maximum: 4)

Number of images to output.

Default: 1

num_inference_steps

integer

(minimum: 1, maximum: 500)

Number of denoising steps

Default: 50

guidance_scale

number

(minimum: 1, maximum: 20)

Scale for classifier-free guidance

Default: 7.5

scheduler

string

Choose a scheduler.

Default: "DPMSolverMultistep"

prompt_strength

number

(minimum: 0, maximum: 1)

Prompt strength when using img2img / inpaint. 1.0 corresponds to full destruction of information in image

Default: 0.8

seed

integer

Random seed. Leave blank to randomize the seed

prompt_mode

string

Choose a prompt mode. Default value prompt uses regular generation while image_prompt uses IP-Adapter to do image prompting.

Default: "prompt"

image_prompt_method

string

Choose a image prompt method: Style only or Style and layout.

Default: "style_and_layout"

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

npx create-replicate --model=replicategithubwc/juggernaut-sdxl

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 replicategithubwc/juggernaut-sdxl using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "replicategithubwc/juggernaut-sdxl:7f15053abd957698ba11bfdd76b450e704c26ba0b8799d8ed36a07a2e5681ea8",
  {
    input: {
      width: 768,
      height: 768,
      prompt: "a photo of an astronaut riding a horse on mars",
      scheduler: "DPMSolverMultistep",
      num_outputs: 1,
      prompt_mode: "prompt",
      guidance_scale: 7.5,
      prompt_strength: 0.8,
      image_prompt_method: "style_and_layout",
      num_inference_steps: 50
    }
  }
);
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 replicategithubwc/juggernaut-sdxl using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "replicategithubwc/juggernaut-sdxl:7f15053abd957698ba11bfdd76b450e704c26ba0b8799d8ed36a07a2e5681ea8",
    input={
        "width": 768,
        "height": 768,
        "prompt": "a photo of an astronaut riding a horse on mars",
        "scheduler": "DPMSolverMultistep",
        "num_outputs": 1,
        "prompt_mode": "prompt",
        "guidance_scale": 7.5,
        "prompt_strength": 0.8,
        "image_prompt_method": "style_and_layout",
        "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 replicategithubwc/juggernaut-sdxl 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": "7f15053abd957698ba11bfdd76b450e704c26ba0b8799d8ed36a07a2e5681ea8",
    "input": {
      "width": 768,
      "height": 768,
      "prompt": "a photo of an astronaut riding a horse on mars",
      "scheduler": "DPMSolverMultistep",
      "num_outputs": 1,
      "prompt_mode": "prompt",
      "guidance_scale": 7.5,
      "prompt_strength": 0.8,
      "image_prompt_method": "style_and_layout",
      "num_inference_steps": 50
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

No output yet! Press "Submit" to start a prediction.

Run time and cost

This model costs approximately $0.057 to run on Replicate, or 17 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker.

This model runs on Nvidia A100 (80GB) GPU hardware. Predictions typically complete within 41 seconds. The predict time for this model varies significantly based on the inputs.

Readme

This model doesn't have a readme.