catacolabs/cartoonify:285cb6c5 – Run with an API on Replicate

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catacolabs /cartoonify:285cb6c5

Playground API

Input

image

*file

Input image

scheduler

string

scheduler

Default: "K_EULER_ANCESTRAL"

num_inference_steps

integer

(minimum: 1, maximum: 500)

Number of denoising steps

Default: 50

guidance_scale

number

(minimum: 1, maximum: 50)

Scale for classifier-free guidance

Default: 7.5

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

refine

string

Which refine style to use

Default: "no_refiner"

high_noise_frac

number

(minimum: 0, maximum: 1)

For expert_ensemble_refiner, the fraction of noise to use

Default: 0.8

seed

integer

Random seed. Leave blank to randomize

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

npx create-replicate --model=catacolabs/cartoonify

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 catacolabs/cartoonify using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "catacolabs/cartoonify:285cb6c5e2ac21bb672a47c0df0373e90bdd4c3a2ffe9937bb6433e81d690fb4",
  {
    input: {
      refine: "no_refiner",
      scheduler: "K_EULER_ANCESTRAL",
      guidance_scale: 7.5,
      high_noise_frac: 0.8,
      prompt_strength: 0.8,
      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 catacolabs/cartoonify using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "catacolabs/cartoonify:285cb6c5e2ac21bb672a47c0df0373e90bdd4c3a2ffe9937bb6433e81d690fb4",
    input={
        "refine": "no_refiner",
        "scheduler": "K_EULER_ANCESTRAL",
        "guidance_scale": 7.5,
        "high_noise_frac": 0.8,
        "prompt_strength": 0.8,
        "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 catacolabs/cartoonify 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": "catacolabs/cartoonify:285cb6c5e2ac21bb672a47c0df0373e90bdd4c3a2ffe9937bb6433e81d690fb4",
    "input": {
      "refine": "no_refiner",
      "scheduler": "K_EULER_ANCESTRAL",
      "guidance_scale": 7.5,
      "high_noise_frac": 0.8,
      "prompt_strength": 0.8,
      "num_inference_steps": 50
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

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