prunaai/flux.1-cheetah – Run with an API on Replicate

Input

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

npx create-replicate --model=prunaai/flux.1-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/flux.1-cheetah using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "prunaai/flux.1-cheetah:40395798681414feaa3bcf8c39bd0e4c12e6b53ce1ec984d52a77e635469d8e5",
  {
    input: {
      seed: 0,
      prompt: "black forest gateau cake spelling out the words \"FLUX DEV\", tasty, food photography, dynamic shot",
      guidance: 3.5,
      go_faster: true,
      go_fast_af: false,
      image_size: 1024,
      aspect_ratio: "1:1",
      output_format: "webp",
      output_quality: 80,
      num_inference_steps: 28
    }
  }
);
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 prunaai/flux.1-cheetah using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "prunaai/flux.1-cheetah:40395798681414feaa3bcf8c39bd0e4c12e6b53ce1ec984d52a77e635469d8e5",
    input={
        "seed": 0,
        "prompt": "black forest gateau cake spelling out the words \"FLUX DEV\", tasty, food photography, dynamic shot",
        "guidance": 3.5,
        "go_faster": True,
        "go_fast_af": False,
        "image_size": 1024,
        "aspect_ratio": "1:1",
        "output_format": "webp",
        "output_quality": 80,
        "num_inference_steps": 28
    }
)
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/flux.1-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": "40395798681414feaa3bcf8c39bd0e4c12e6b53ce1ec984d52a77e635469d8e5",
    "input": {
      "seed": 0,
      "prompt": "black forest gateau cake spelling out the words \\"FLUX DEV\\", tasty, food photography, dynamic shot",
      "guidance": 3.5,
      "go_faster": true,
      "go_fast_af": false,
      "image_size": 1024,
      "aspect_ratio": "1:1",
      "output_format": "webp",
      "output_quality": 80,
      "num_inference_steps": 28
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

Output

Generated in

2.0 seconds

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Run time and cost

This model costs approximately $0.0026 to run on Replicate, or 384 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker.

This model runs on Nvidia H100 GPU hardware. Predictions typically complete within 2 seconds.