prunaai/sdxl-cheetah:0e8c6bd5 – Run with an API on Replicate

Version

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prunaai /sdxl-cheetah:0e8c6bd5

Playground API

Input

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

npx create-replicate --model=prunaai/sdxl-cheetah

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

const output = await replicate.run(
  "prunaai/sdxl-cheetah:0e8c6bd5247a7ef1eefc8bfc088cc0354bc49f89f3caf3f472344886ffa42b62",
  {
    input: {
      seed: 42,
      speed: 0.5,
      num_images: 1,
      image_width: 1024,
      image_height: 1024,
      guidance_scale: 7.5,
      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 prunaai/sdxl-cheetah using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "prunaai/sdxl-cheetah:0e8c6bd5247a7ef1eefc8bfc088cc0354bc49f89f3caf3f472344886ffa42b62",
    input={
        "seed": 42,
        "speed": 0.5,
        "num_images": 1,
        "image_width": 1024,
        "image_height": 1024,
        "guidance_scale": 7.5,
        "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 prunaai/sdxl-cheetah 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": "0e8c6bd5247a7ef1eefc8bfc088cc0354bc49f89f3caf3f472344886ffa42b62",
    "input": {
      "seed": 42,
      "speed": 0.5,
      "num_images": 1,
      "image_width": 1024,
      "image_height": 1024,
      "guidance_scale": 7.5,
      "num_inference_steps": 50
    }
  }' \
  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/prunaai/sdxl-cheetah@sha256:0e8c6bd5247a7ef1eefc8bfc088cc0354bc49f89f3caf3f472344886ffa42b62 \
  -i 'seed=42' \
  -i 'speed=0.5' \
  -i 'num_images=1' \
  -i 'image_width=1024' \
  -i 'image_height=1024' \
  -i 'guidance_scale=7.5' \
  -i 'num_inference_steps=50'

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/prunaai/sdxl-cheetah@sha256:0e8c6bd5247a7ef1eefc8bfc088cc0354bc49f89f3caf3f472344886ffa42b62
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "seed": 42,
      "speed": 0.5,
      "num_images": 1,
      "image_width": 1024,
      "image_height": 1024,
      "guidance_scale": 7.5,
      "num_inference_steps": 50
    }
  }' \
  http://localhost:5000/predictions

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

Output

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