fire/flux:c0242c7f – Run with an API on Replicate

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fire /flux:c0242c7f

Playground API

Input

prompt

*string

Shift + Return to add a new line

Prompt for generated image

aspect_ratio

string

Aspect ratio for the generated image

Default: "2:1"

num_outputs

integer

(minimum: 1, maximum: 4)

Number of outputs to generate

Default: 1

num_inference_steps

integer

(minimum: 1, maximum: 8)

Number of denoising steps. 8 is recommended, and lower number of steps produce lower quality outputs, faster.

Default: 8

seed

integer

Random seed. Set for reproducible generation

output_format

string

Format of the output images

Default: "webp"

output_quality

integer

(minimum: 0, maximum: 100)

Quality when saving the output images, from 0 to 100. 100 is best quality, 0 is lowest quality. Not relevant for .png outputs

Default: 80

disable_safety_checker

boolean

Disable safety checker for generated images.

Default: false

go_fast

boolean

Run faster predictions with model optimized for speed (currently fp8 quantized); disable to run in original bf16

Default: true

megapixels

string

Approximate number of megapixels for generated image

Default: "1"

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

npx create-replicate --model=fire/flux

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

const output = await replicate.run(
  "fire/flux:c0242c7f840f0950ef3bf09a77c0804554b00e0d6c9e270ed66136e4bbfa048b",
  {
    input: {
      go_fast: true,
      megapixels: "1",
      num_outputs: 1,
      aspect_ratio: "2:1",
      output_format: "webp",
      output_quality: 80,
      num_inference_steps: 8
    }
  }
);

// To access the file URL:
console.log(output[0].url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", output[0]);

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

output = replicate.run(
    "fire/flux:c0242c7f840f0950ef3bf09a77c0804554b00e0d6c9e270ed66136e4bbfa048b",
    input={
        "go_fast": True,
        "megapixels": "1",
        "num_outputs": 1,
        "aspect_ratio": "2:1",
        "output_format": "webp",
        "output_quality": 80,
        "num_inference_steps": 8
    }
)
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 fire/flux 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": "c0242c7f840f0950ef3bf09a77c0804554b00e0d6c9e270ed66136e4bbfa048b",
    "input": {
      "go_fast": true,
      "megapixels": "1",
      "num_outputs": 1,
      "aspect_ratio": "2:1",
      "output_format": "webp",
      "output_quality": 80,
      "num_inference_steps": 8
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

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