nightmareai/majesty-diffusion:b495ac4d – Run with an API on Replicate

Version

You're looking at a specific version of this model. Jump to the model overview.

nightmareai /majesty-diffusion:b495ac4d

Input

clip_prompt

string

Shift + Return to add a new line

The portrait of a Majestic Princess, trending on artstationThe portrait of a Majestic Princess, trending on artstation

Prompt for CLIP guidance

Default: "The portrait of a Majestic Princess, trending on artstation"

latent_prompt

string

Shift + Return to add a new line

The portrait of a Majestic Princess, trending on artstationThe portrait of a Majestic Princess, trending on artstation

Prompt for latent diffusion

Default: "The portrait of a Majestic Princess, trending on artstation"

model

string

Latent diffusion model

Default: "finetuned"

latent_negatives

string

Shift + Return to add a new line

Negative prompts for Latent Diffusion

Default: ""

height

integer

Output height (output will be scaled up 1.5x with default settings)

Default: 256

width

integer

Output width (output will be scaled up 1.5x with default settings)

Default: 256

init_image

file

Initial image

init_mask

file

A mask same width and height as the original image with the color black indicating where to inpaint

init_scale

integer

Controls how much the init image should influence the final result. Experiment with values around 1000

Default: 1000

init_brightness

number

Init image brightness

Default: 0

latent_scale

integer

The `latent_diffusion_guidance_scale` will determine how much the `latent_prompts` affect the image. Lower help with text interpretation, higher help with composition. Try values between 0-15. If you see too much text, lower it

Default: 12

clip_scale

integer

CLIP guidance scale

Default: 16000

aesthetic_loss_scale

integer

Aesthetic loss scale

Default: 400

starting_timestep

number

Starting timestep

Default: 0.9

num_batches

integer

(minimum: 1, maximum: 10)

Number of batches

Default: 1

custom_settings

file

Advanced settings file

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

npx create-replicate --model=nightmareai/majesty-diffusion

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 nightmareai/majesty-diffusion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "nightmareai/majesty-diffusion:b495ac4d7237d90d70d4b964260acf151e8c5c6587e29ebc15c6f898fabe5a01",
  {
    input: {
      model: "finetuned",
      width: 256,
      height: 256,
      clip_scale: 16000,
      init_scale: 1000,
      clip_prompt: "The portrait of a Majestic Princess, trending on artstation",
      num_batches: 1,
      latent_scale: 12,
      latent_prompt: "The portrait of a Majestic Princess, trending on artstation",
      init_brightness: 0,
      latent_negatives: "",
      starting_timestep: 0.9,
      aesthetic_loss_scale: 400
    }
  }
);

// To access the file URL:
console.log(output[0].url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", output[0]);

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 nightmareai/majesty-diffusion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "nightmareai/majesty-diffusion:b495ac4d7237d90d70d4b964260acf151e8c5c6587e29ebc15c6f898fabe5a01",
    input={
        "model": "finetuned",
        "width": 256,
        "height": 256,
        "clip_scale": 16000,
        "init_scale": 1000,
        "clip_prompt": "The portrait of a Majestic Princess, trending on artstation",
        "num_batches": 1,
        "latent_scale": 12,
        "latent_prompt": "The portrait of a Majestic Princess, trending on artstation",
        "init_brightness": 0,
        "latent_negatives": "",
        "starting_timestep": 0.9,
        "aesthetic_loss_scale": 400
    }
)
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 nightmareai/majesty-diffusion 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": "b495ac4d7237d90d70d4b964260acf151e8c5c6587e29ebc15c6f898fabe5a01",
    "input": {
      "model": "finetuned",
      "width": 256,
      "height": 256,
      "clip_scale": 16000,
      "init_scale": 1000,
      "clip_prompt": "The portrait of a Majestic Princess, trending on artstation",
      "num_batches": 1,
      "latent_scale": 12,
      "latent_prompt": "The portrait of a Majestic Princess, trending on artstation",
      "init_brightness": 0,
      "latent_negatives": "",
      "starting_timestep": 0.9,
      "aesthetic_loss_scale": 400
    }
  }' \
  https://api.replicate.com/v1/predictions

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

You can run this model locally using Cog. First, install Cog:

brew install cog

If you don’t have Homebrew, there are other installation options available.

Run this to download the model and run it in your local environment:

cog predict r8.im/nightmareai/majesty-diffusion@sha256:b495ac4d7237d90d70d4b964260acf151e8c5c6587e29ebc15c6f898fabe5a01 \
  -i 'model="finetuned"' \
  -i 'width=256' \
  -i 'height=256' \
  -i 'clip_scale=16000' \
  -i 'init_scale=1000' \
  -i 'clip_prompt="The portrait of a Majestic Princess, trending on artstation"' \
  -i 'num_batches=1' \
  -i 'latent_scale=12' \
  -i 'latent_prompt="The portrait of a Majestic Princess, trending on artstation"' \
  -i 'init_brightness=0' \
  -i 'latent_negatives=""' \
  -i 'starting_timestep=0.9' \
  -i 'aesthetic_loss_scale=400'

To learn more, take a look at the Cog documentation.

Run this to download the model and run it in your local environment:

docker run -d -p 5000:5000 --gpus=all r8.im/nightmareai/majesty-diffusion@sha256:b495ac4d7237d90d70d4b964260acf151e8c5c6587e29ebc15c6f898fabe5a01
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "model": "finetuned",
      "width": 256,
      "height": 256,
      "clip_scale": 16000,
      "init_scale": 1000,
      "clip_prompt": "The portrait of a Majestic Princess, trending on artstation",
      "num_batches": 1,
      "latent_scale": 12,
      "latent_prompt": "The portrait of a Majestic Princess, trending on artstation",
      "init_brightness": 0,
      "latent_negatives": "",
      "starting_timestep": 0.9,
      "aesthetic_loss_scale": 400
    }
  }' \
  http://localhost:5000/predictions

To learn more, take a look at the Cog documentation.

Output

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