zsxkib/sd3-controlnet:84600cf2 – Run with an API on Replicate

Version

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zsxkib /sd3-controlnet:84600cf2

Playground API

Input

input_image

*file

Input image

prompt

*string

Shift + Return to add a new line

Prompt

negative_prompt

string

Shift + Return to add a new line

Negative prompt

Default: "NSFW, nude, naked, porn, ugly"

inference_steps

integer

(minimum: 1, maximum: 50)

Inference steps

Default: 25

guidance_scale

number

(minimum: 1, maximum: 10)

Guidance scale

Default: 7

control_weight

number

(minimum: 0, maximum: 1)

Control weight

Default: 0.7

seed

integer

Random seed. Leave blank to randomize the seed

output_format

string

Format of the output images

Default: "webp"

output_quality

integer

(minimum: 0, maximum: 100)

Quality of the output images, from 0 to 100. 100 is best quality, 0 is lowest quality.

Default: 80

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

npx create-replicate --model=zsxkib/sd3-controlnet

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 zsxkib/sd3-controlnet using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "zsxkib/sd3-controlnet:84600cf2354cdd9147d1484cf24c8f73f826e3b78e31802c69347ef46a03d9ae",
  {
    input: {
      output_format: "webp",
      control_weight: 0.7,
      guidance_scale: 7,
      output_quality: 80,
      inference_steps: 25,
      negative_prompt: "NSFW, nude, naked, porn, ugly"
    }
  }
);
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 zsxkib/sd3-controlnet using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "zsxkib/sd3-controlnet:84600cf2354cdd9147d1484cf24c8f73f826e3b78e31802c69347ef46a03d9ae",
    input={
        "output_format": "webp",
        "control_weight": 0.7,
        "guidance_scale": 7,
        "output_quality": 80,
        "inference_steps": 25,
        "negative_prompt": "NSFW, nude, naked, porn, ugly"
    }
)
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 zsxkib/sd3-controlnet 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": "84600cf2354cdd9147d1484cf24c8f73f826e3b78e31802c69347ef46a03d9ae",
    "input": {
      "output_format": "webp",
      "control_weight": 0.7,
      "guidance_scale": 7,
      "output_quality": 80,
      "inference_steps": 25,
      "negative_prompt": "NSFW, nude, naked, porn, ugly"
    }
  }' \
  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/zsxkib/sd3-controlnet@sha256:84600cf2354cdd9147d1484cf24c8f73f826e3b78e31802c69347ef46a03d9ae \
  -i 'output_format="webp"' \
  -i 'control_weight=0.7' \
  -i 'guidance_scale=7' \
  -i 'output_quality=80' \
  -i 'inference_steps=25' \
  -i 'negative_prompt="NSFW, nude, naked, porn, ugly"'

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/zsxkib/sd3-controlnet@sha256:84600cf2354cdd9147d1484cf24c8f73f826e3b78e31802c69347ef46a03d9ae
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "output_format": "webp",
      "control_weight": 0.7,
      "guidance_scale": 7,
      "output_quality": 80,
      "inference_steps": 25,
      "negative_prompt": "NSFW, nude, naked, porn, ugly"
    }
  }' \
  http://localhost:5000/predictions

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

Output

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