hardikdava/flux-image-editing:f3c783b2 | Run with an API on Replicate

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hardikdava /flux-image-editing:f3c783b2

Playground API

Input

prompt

*string

Shift + Return to add a new line

Prompt for generated image

image

file

The image for the generation

guidance_scale

number

(minimum: 0, maximum: 50)

Guidance scale

Default: 30

num_inference_steps

integer

(minimum: 1, maximum: 80)

Number of inference steps

Default: 50

seed

integer

Random seed. Set for reproducible generation

num_outputs

integer

(minimum: 1, maximum: 4)

Number of outputs to generate

Default: 1

use_hyper_lora

boolean

Use Hyper Lora for faster generation. This speeds up the process.

Default: false

output_format

string

Format of the output images

Default: "jpg"

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: 100

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

npx create-replicate --model=hardikdava/flux-image-editing

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

const output = await replicate.run(
  "hardikdava/flux-image-editing:f3c783b24381c61681c97814f6501c1afc263cc78d7f3d04ffd4e9914977ece8",
  {
    input: {
      num_outputs: 1,
      output_format: "jpg",
      guidance_scale: 30,
      output_quality: 100,
      use_hyper_lora: false,
      num_inference_steps: 50
    }
  }
);

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

output = replicate.run(
    "hardikdava/flux-image-editing:f3c783b24381c61681c97814f6501c1afc263cc78d7f3d04ffd4e9914977ece8",
    input={
        "num_outputs": 1,
        "output_format": "jpg",
        "guidance_scale": 30,
        "output_quality": 100,
        "use_hyper_lora": False,
        "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 hardikdava/flux-image-editing 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": "hardikdava/flux-image-editing:f3c783b24381c61681c97814f6501c1afc263cc78d7f3d04ffd4e9914977ece8",
    "input": {
      "num_outputs": 1,
      "output_format": "jpg",
      "guidance_scale": 30,
      "output_quality": 100,
      "use_hyper_lora": false,
      "num_inference_steps": 50
    }
  }' \
  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.