zylim0702/multi_controlnet_inpainting_stable_diffusion:f4e9b0c1

Version

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

zylim0702 /multi_controlnet_inpainting_stable_diffusion:f4e9b0c1

Playground API

Input

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

npx create-replicate --model=zylim0702/multi_controlnet_inpainting_stable_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";
import fs from "node:fs";

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

Run zylim0702/multi_controlnet_inpainting_stable_diffusion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "zylim0702/multi_controlnet_inpainting_stable_diffusion:f4e9b0c1fe4406a4a610959cadc4c5f1db6e9235b19a4c467ec10a415ffb96e4",
  {
    input: {
      controlnet_type: "canny",
      num_inference_steps: 20,
      controlnet_conditioning_scale: 0.25
    }
  }
);

// 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 zylim0702/multi_controlnet_inpainting_stable_diffusion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "zylim0702/multi_controlnet_inpainting_stable_diffusion:f4e9b0c1fe4406a4a610959cadc4c5f1db6e9235b19a4c467ec10a415ffb96e4",
    input={
        "controlnet_type": "canny",
        "num_inference_steps": 20,
        "controlnet_conditioning_scale": 0.25
    }
)
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 zylim0702/multi_controlnet_inpainting_stable_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": "zylim0702/multi_controlnet_inpainting_stable_diffusion:f4e9b0c1fe4406a4a610959cadc4c5f1db6e9235b19a4c467ec10a415ffb96e4",
    "input": {
      "controlnet_type": "canny",
      "num_inference_steps": 20,
      "controlnet_conditioning_scale": 0.25
    }
  }' \
  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.