prunaai/stable-diffusion-cheetah – Run with an API on Replicate

prunaai / stable-diffusion-cheetah

This model is an optimised version of stable-diffusion by stability AI that is 3x faster and 3x cheaper.

Cold

Public
160 runs
A100 (80GB)

Run with an API

Playground API Examples README Versions

Input

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

npx create-replicate --model=prunaai/stable-diffusion-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/stable-diffusion-cheetah using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "prunaai/stable-diffusion-cheetah:27b76b3c3b98fc7cf55b115796573022f8e9df4c1cf5e42c24a82796496614e1",
  {
    input: {
      seed: -1,
      prompt: "a red apple on a table",
      go_fast_af: false,
      num_images: 1,
      image_width: 512,
      image_height: 512,
      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/stable-diffusion-cheetah using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "prunaai/stable-diffusion-cheetah:27b76b3c3b98fc7cf55b115796573022f8e9df4c1cf5e42c24a82796496614e1",
    input={
        "seed": -1,
        "prompt": "a red apple on a table",
        "go_fast_af": False,
        "num_images": 1,
        "image_width": 512,
        "image_height": 512,
        "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/stable-diffusion-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": "27b76b3c3b98fc7cf55b115796573022f8e9df4c1cf5e42c24a82796496614e1",
    "input": {
      "seed": -1,
      "prompt": "a red apple on a table",
      "go_fast_af": false,
      "num_images": 1,
      "image_width": 512,
      "image_height": 512,
      "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.

Output

Generated in

0.6 seconds

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This output was created using a different version of the model, prunaai/stable-diffusion-cheetah:bce45013.

Examples

View more examples

Run time and cost

This model runs on Nvidia A100 (80GB) GPU hardware. We don't yet have enough runs of this model to provide performance information.

Readme

This model doesn't have a readme.