yuni-eng/controlnet-sdxl:c1da899c | Run with an API on Replicate

Version

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

yuni-eng /controlnet-sdxl:c1da899c

Playground API

Input

image

file

Input image to create in different art medium

prompt

string

Shift + Return to add a new line

Input your imagination

Default: ""

negative_prompt

string

Shift + Return to add a new line

poorly drawn hands, poorly drawn feet, poorly drawn face, out of frame, extra limbs, disfigured, deformed, body out of frame, bad anatomy, signature, cut off, low contrast, underexposed, overexposed, bad art, beginner, amateur, distorted face, blurry, draft, grainypoorly drawn hands, poorly drawn feet, poorly drawn face, out of frame, extra limbs, disfigured, deformed, body out of frame, bad anatomy, signature, cut off, low contrast, underexposed, overexposed, bad art, beginner, amateur, distorted face, blurry, draft, grainy

Specify things to not see in the output

Default: "poorly drawn hands, poorly drawn feet, poorly drawn face, out of frame, extra limbs, disfigured, deformed, body out of frame, bad anatomy, signature, cut off, low contrast, underexposed, overexposed, bad art, beginner, amateur, distorted face, blurry, draft, grainy"

width

integer

Width of output image. Maximum size is 1024x768 or 768x1024 because of memory limits

Default: 768

height

integer

Height of output image. Maximum size is 1024x768 or 768x1024 because of memory limits

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

condition_scale

number

(minimum: 0, maximum: 1)

controlnet conditioning scale for generalization

Default: 0.5

art_medium

string

Choose an art medium.

Default: "line art"

seed

integer

Random seed. Set to 0 to randomize the seed

Default: 0

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

npx create-replicate --model=yuni-eng/controlnet-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";
import fs from "node:fs";

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

Run yuni-eng/controlnet-sdxl using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "yuni-eng/controlnet-sdxl:c1da899cc2025aa682c6691ea98dabb3833a735bcdef574823ac3dab1acbd057",
  {
    input: {
      seed: 0,
      width: 768,
      height: 768,
      prompt: "",
      art_medium: "line art",
      num_outputs: 1,
      condition_scale: 0.5,
      negative_prompt: "poorly drawn hands, poorly drawn feet, poorly drawn face, out of frame, extra limbs, disfigured, deformed, body out of frame, bad anatomy, signature, cut off, low contrast, underexposed, overexposed, bad art, beginner, amateur, distorted face, blurry, draft, grainy",
      num_inference_steps: 50
    }
  }
);

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

output = replicate.run(
    "yuni-eng/controlnet-sdxl:c1da899cc2025aa682c6691ea98dabb3833a735bcdef574823ac3dab1acbd057",
    input={
        "seed": 0,
        "width": 768,
        "height": 768,
        "prompt": "",
        "art_medium": "line art",
        "num_outputs": 1,
        "condition_scale": 0.5,
        "negative_prompt": "poorly drawn hands, poorly drawn feet, poorly drawn face, out of frame, extra limbs, disfigured, deformed, body out of frame, bad anatomy, signature, cut off, low contrast, underexposed, overexposed, bad art, beginner, amateur, distorted face, blurry, draft, grainy",
        "num_inference_steps": 50
    }
)

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

# To write the file to disk:
with open("my-image.png", "wb") as file:
    file.write(output[0].read())

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 yuni-eng/controlnet-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": "yuni-eng/controlnet-sdxl:c1da899cc2025aa682c6691ea98dabb3833a735bcdef574823ac3dab1acbd057",
    "input": {
      "seed": 0,
      "width": 768,
      "height": 768,
      "prompt": "",
      "art_medium": "line art",
      "num_outputs": 1,
      "condition_scale": 0.5,
      "negative_prompt": "poorly drawn hands, poorly drawn feet, poorly drawn face, out of frame, extra limbs, disfigured, deformed, body out of frame, bad anatomy, signature, cut off, low contrast, underexposed, overexposed, bad art, beginner, amateur, distorted face, blurry, draft, grainy",
      "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.