prunaai/flux.1-juiced | 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-juiced

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 prunaai/flux.1-juiced 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-juiced:6c7af2f8c6ad10467ac22f5f9cc892f4ef789e071d64f19199d5cc070cf6a32d",
  {
    input: {
      seed: 2,
      prompt: "a tiny astronaut hatching from an egg on the moon",
      guidance: 3.5,
      image_size: 1024,
      speed_mode: "Extra Juiced 🔥 (more speed)",
      aspect_ratio: "1:1",
      output_format: "webp",
      output_quality: 80,
      num_inference_steps: 28
    }
  }
);

// 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/flux.1-juiced using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "prunaai/flux.1-juiced:6c7af2f8c6ad10467ac22f5f9cc892f4ef789e071d64f19199d5cc070cf6a32d",
    input={
        "seed": 2,
        "prompt": "a tiny astronaut hatching from an egg on the moon",
        "guidance": 3.5,
        "image_size": 1024,
        "speed_mode": "Extra Juiced 🔥 (more speed)",
        "aspect_ratio": "1:1",
        "output_format": "webp",
        "output_quality": 80,
        "num_inference_steps": 28
    }
)

# To access the file URL:
print(output.url())
#=> "http://example.com"

# To write the file to disk:
with open("my-image.png", "wb") as file:
    file.write(output.read())

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-juiced 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": "prunaai/flux.1-juiced:6c7af2f8c6ad10467ac22f5f9cc892f4ef789e071d64f19199d5cc070cf6a32d",
    "input": {
      "seed": 2,
      "prompt": "a tiny astronaut hatching from an egg on the moon",
      "guidance": 3.5,
      "image_size": 1024,
      "speed_mode": "Extra Juiced 🔥 (more speed)",
      "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

1.7 seconds

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Examples

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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. The predict time for this model varies significantly based on the inputs.

Readme

This model doesn't have a readme.