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fofr /sandbox:f6800331

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single_blocks.37.modulation.lin.bias

Default: 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gle_blocks.22.linear2.weight=1.0\nsingle_blocks.22.linear2.bias=1.0\nsingle_blocks.22.modulation.lin.weight=1.0\nsingle_blocks.22.modulation.lin.bias=1.0\nsingle_blocks.23.linear1.weight=1.0\nsingle_blocks.23.linear1.bias=1.0\nsingle_blocks.23.linear2.weight=1.0\nsingle_blocks.23.linear2.bias=1.0\nsingle_blocks.23.modulation.lin.weight=1.0\nsingle_blocks.23.modulation.lin.bias=1.0\nsingle_blocks.24.linear1.weight=1.0\nsingle_blocks.24.linear1.bias=1.0\nsingle_blocks.24.linear2.weight=1.0\nsingle_blocks.24.linear2.bias=1.0\nsingle_blocks.24.modulation.lin.weight=1.0\nsingle_blocks.24.modulation.lin.bias=1.0\nsingle_blocks.25.linear1.weight=1.0\nsingle_blocks.25.linear1.bias=1.0\nsingle_blocks.25.linear2.weight=1.0\nsingle_blocks.25.linear2.bias=1.0\nsingle_blocks.25.modulation.lin.weight=1.0\nsingle_blocks.25.modulation.lin.bias=1.0\nsingle_blocks.26.linear1.weight=1.0\nsingle_blocks.26.linear1.bias=1.0\nsingle_blocks.26.linear2.weight=1.0\nsingle_blocks.26.linear2.bias=1.0\nsingle_blocks.26.modulation.lin.weight=1.0\nsingle_blocks.26.modulation.lin.bias=1.0\nsingle_blocks.27.linear1.weight=1.0\nsingle_blocks.27.linear1.bias=1.0\nsingle_blocks.27.linear2.weight=1.0\nsingle_blocks.27.linear2.bias=1.0\nsingle_blocks.27.modulation.lin.weight=1.0\nsingle_blocks.27.modulation.lin.bias=1.0\nsingle_blocks.28.linear1.weight=1.0\nsingle_blocks.28.linear1.bias=1.0\nsingle_blocks.28.linear2.weight=1.0\nsingle_blocks.28.linear2.bias=1.0\nsingle_blocks.28.modulation.lin.weight=1.0\nsingle_blocks.28.modulation.lin.bias=1.0\nsingle_blocks.29.linear1.weight=1.0\nsingle_blocks.29.linear1.bias=1.0\nsingle_blocks.29.linear2.weight=1.0\nsingle_blocks.29.linear2.bias=1.0\nsingle_blocks.29.modulation.lin.weight=1.0\nsingle_blocks.29.modulation.lin.bias=1.0\nsingle_blocks.30.linear1.weight=1.0\nsingle_blocks.30.linear1.bias=1.0\nsingle_blocks.30.linear2.weight=1.0\nsingle_blocks.30.linear2.bias=1.0\nsingle_blocks.30.modulation.lin.weight=1.0\nsingle_blocks.30.modulation.lin.bias=1.0\nsingle_blocks.31.linear1.weight=1.0\nsingle_blocks.31.linear1.bias=1.0\nsingle_blocks.31.linear2.weight=1.0\nsingle_blocks.31.linear2.bias=1.0\nsingle_blocks.31.modulation.lin.weight=1.0\nsingle_blocks.31.modulation.lin.bias=1.0\nsingle_blocks.32.linear1.weight=1.0\nsingle_blocks.32.linear1.bias=1.0\nsingle_blocks.32.linear2.weight=1.0\nsingle_blocks.32.linear2.bias=1.0\nsingle_blocks.32.modulation.lin.weight=1.0\nsingle_blocks.32.modulation.lin.bias=1.0\nsingle_blocks.33.linear1.weight=1.0\nsingle_blocks.33.linear1.bias=1.0\nsingle_blocks.33.linear2.weight=1.0\nsingle_blocks.33.linear2.bias=1.0\nsingle_blocks.33.modulation.lin.weight=1.0\nsingle_blocks.33.modulation.lin.bias=1.0\nsingle_blocks.34.linear1.weight=1.0\nsingle_blocks.34.linear1.bias=1.0\nsingle_blocks.34.linear2.weight=1.0\nsingle_blocks.34.linear2.bias=1.0\nsingle_blocks.34.modulation.lin.weight=1.0\nsingle_blocks.34.modulation.lin.bias=1.0\nsingle_blocks.35.linear1.weight=1.0\nsingle_blocks.35.linear1.bias=1.0\nsingle_blocks.35.linear2.weight=1.0\nsingle_blocks.35.linear2.bias=1.0\nsingle_blocks.35.modulation.lin.weight=1.0\nsingle_blocks.35.modulation.lin.bias=1.0\nsingle_blocks.36.linear1.weight=1.0\nsingle_blocks.36.linear1.bias=1.0\nsingle_blocks.36.linear2.weight=1.0\nsingle_blocks.36.linear2.bias=1.0\nsingle_blocks.36.modulation.lin.weight=1.0\nsingle_blocks.36.modulation.lin.bias=1.0\nsingle_blocks.37.linear1.weight=1.0\nsingle_blocks.37.linear1.bias=1.0\nsingle_blocks.37.linear2.weight=1.0\nsingle_blocks.37.linear2.bias=1.0\nsingle_blocks.37.modulation.lin.weight=1.0\nsingle_blocks.37.modulation.lin.bias"

flux_model_layers_to_patch

string

An enumeration.

Default: "all"

flux_model_layers_value

number

(minimum: 0, maximum: 2)

The new value for the selected layers

Default: 1.01

weights_and_biases_to_patch

string

An enumeration.

Default: "weights and biases"

flux_model_layers_regular_expressions

string[]

Default: []

aspect_ratio

string

Aspect ratio for the generated image in text-to-image mode. The size will always be 1 megapixel, i.e. 1024x1024 if aspect ratio is 1:1. To use arbitrary width and height, set aspect ratio to 'custom'. Note: Ignored in img2img and inpainting modes.

Default: "1:1"

num_outputs

integer

(minimum: 1, maximum: 4)

Number of images to output.

Default: 1

num_inference_steps

integer

(minimum: 1, maximum: 50)

Number of inference steps. More steps can give more detailed images, but take longer.

Default: 28

guidance_scale

number

(minimum: 0, maximum: 10)

Guidance scale for the diffusion process. Lower values can give more realistic images. Good values to try are 2, 2.5, 3 and 3.5

Default: 3

max_shift

number

(minimum: 0, maximum: 10)

Maximum shift

Default: 1.15

base_shift

number

(minimum: 0, maximum: 10)

Base shift

Default: 0.5

output_format

string

Format of the output images

Default: "webp"

output_quality

integer

(minimum: 0, maximum: 100)

Quality of the output images, from 0 to 100. 100 is best quality, 0 is lowest quality.

Default: 95

seed

integer

Set a seed for reproducibility. Random by default.

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

npx create-replicate --model=fofr/sandbox

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

const output = await replicate.run(
  "fofr/sandbox:f68003314c9da95a133e95cea39a81e92a4e4b724ce57ac2efd29ec196f49e6d",
  {
    input: {
      max_shift: 1.15,
      base_shift: 0.5,
      num_outputs: 1,
      aspect_ratio: "1:1",
      output_format: "webp",
      guidance_scale: 3,
      output_quality: 95,
      num_inference_steps: 28,
      flux_layers_to_patch: 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gle_blocks.22.linear2.weight=1.0\nsingle_blocks.22.linear2.bias=1.0\nsingle_blocks.22.modulation.lin.weight=1.0\nsingle_blocks.22.modulation.lin.bias=1.0\nsingle_blocks.23.linear1.weight=1.0\nsingle_blocks.23.linear1.bias=1.0\nsingle_blocks.23.linear2.weight=1.0\nsingle_blocks.23.linear2.bias=1.0\nsingle_blocks.23.modulation.lin.weight=1.0\nsingle_blocks.23.modulation.lin.bias=1.0\nsingle_blocks.24.linear1.weight=1.0\nsingle_blocks.24.linear1.bias=1.0\nsingle_blocks.24.linear2.weight=1.0\nsingle_blocks.24.linear2.bias=1.0\nsingle_blocks.24.modulation.lin.weight=1.0\nsingle_blocks.24.modulation.lin.bias=1.0\nsingle_blocks.25.linear1.weight=1.0\nsingle_blocks.25.linear1.bias=1.0\nsingle_blocks.25.linear2.weight=1.0\nsingle_blocks.25.linear2.bias=1.0\nsingle_blocks.25.modulation.lin.weight=1.0\nsingle_blocks.25.modulation.lin.bias=1.0\nsingle_blocks.26.linear1.weight=1.0\nsingle_blocks.26.linear1.bias=1.0\nsingle_blocks.26.linear2.weight=1.0\nsingle_blocks.26.linear2.bias=1.0\nsingle_blocks.26.modulation.lin.weight=1.0\nsingle_blocks.26.modulation.lin.bias=1.0\nsingle_blocks.27.linear1.weight=1.0\nsingle_blocks.27.linear1.bias=1.0\nsingle_blocks.27.linear2.weight=1.0\nsingle_blocks.27.linear2.bias=1.0\nsingle_blocks.27.modulation.lin.weight=1.0\nsingle_blocks.27.modulation.lin.bias=1.0\nsingle_blocks.28.linear1.weight=1.0\nsingle_blocks.28.linear1.bias=1.0\nsingle_blocks.28.linear2.weight=1.0\nsingle_blocks.28.linear2.bias=1.0\nsingle_blocks.28.modulation.lin.weight=1.0\nsingle_blocks.28.modulation.lin.bias=1.0\nsingle_blocks.29.linear1.weight=1.0\nsingle_blocks.29.linear1.bias=1.0\nsingle_blocks.29.linear2.weight=1.0\nsingle_blocks.29.linear2.bias=1.0\nsingle_blocks.29.modulation.lin.weight=1.0\nsingle_blocks.29.modulation.lin.bias=1.0\nsingle_blocks.30.linear1.weight=1.0\nsingle_blocks.30.linear1.bias=1.0\nsingle_blocks.30.linear2.weight=1.0\nsingle_blocks.30.linear2.bias=1.0\nsingle_blocks.30.modulation.lin.weight=1.0\nsingle_blocks.30.modulation.lin.bias=1.0\nsingle_blocks.31.linear1.weight=1.0\nsingle_blocks.31.linear1.bias=1.0\nsingle_blocks.31.linear2.weight=1.0\nsingle_blocks.31.linear2.bias=1.0\nsingle_blocks.31.modulation.lin.weight=1.0\nsingle_blocks.31.modulation.lin.bias=1.0\nsingle_blocks.32.linear1.weight=1.0\nsingle_blocks.32.linear1.bias=1.0\nsingle_blocks.32.linear2.weight=1.0\nsingle_blocks.32.linear2.bias=1.0\nsingle_blocks.32.modulation.lin.weight=1.0\nsingle_blocks.32.modulation.lin.bias=1.0\nsingle_blocks.33.linear1.weight=1.0\nsingle_blocks.33.linear1.bias=1.0\nsingle_blocks.33.linear2.weight=1.0\nsingle_blocks.33.linear2.bias=1.0\nsingle_blocks.33.modulation.lin.weight=1.0\nsingle_blocks.33.modulation.lin.bias=1.0\nsingle_blocks.34.linear1.weight=1.0\nsingle_blocks.34.linear1.bias=1.0\nsingle_blocks.34.linear2.weight=1.0\nsingle_blocks.34.linear2.bias=1.0\nsingle_blocks.34.modulation.lin.weight=1.0\nsingle_blocks.34.modulation.lin.bias=1.0\nsingle_blocks.35.linear1.weight=1.0\nsingle_blocks.35.linear1.bias=1.0\nsingle_blocks.35.linear2.weight=1.0\nsingle_blocks.35.linear2.bias=1.0\nsingle_blocks.35.modulation.lin.weight=1.0\nsingle_blocks.35.modulation.lin.bias=1.0\nsingle_blocks.36.linear1.weight=1.0\nsingle_blocks.36.linear1.bias=1.0\nsingle_blocks.36.linear2.weight=1.0\nsingle_blocks.36.linear2.bias=1.0\nsingle_blocks.36.modulation.lin.weight=1.0\nsingle_blocks.36.modulation.lin.bias=1.0\nsingle_blocks.37.linear1.weight=1.0\nsingle_blocks.37.linear1.bias=1.0\nsingle_blocks.37.linear2.weight=1.0\nsingle_blocks.37.linear2.bias=1.0\nsingle_blocks.37.modulation.lin.weight=1.0\nsingle_blocks.37.modulation.lin.bias",
      flux_model_layers_value: 1.01,
      flux_model_layers_to_patch: "all",
      weights_and_biases_to_patch: "weights and biases",
      flux_model_layers_regular_expressions: []
    }
  }
);

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

output = replicate.run(
    "fofr/sandbox:f68003314c9da95a133e95cea39a81e92a4e4b724ce57ac2efd29ec196f49e6d",
    input={
        "max_shift": 1.15,
        "base_shift": 0.5,
        "num_outputs": 1,
        "aspect_ratio": "1:1",
        "output_format": "webp",
        "guidance_scale": 3,
        "output_quality": 95,
        "num_inference_steps": 28,
        "flux_layers_to_patch": 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e_blocks.0.linear2.weight=1.0\nsingle_blocks.0.linear2.bias=1.0\nsingle_blocks.0.modulation.lin.weight=1.0\nsingle_blocks.0.modulation.lin.bias=1.0\nsingle_blocks.1.linear1.weight=1.0\nsingle_blocks.1.linear1.bias=1.0\nsingle_blocks.1.linear2.weight=1.0\nsingle_blocks.1.linear2.bias=1.0\nsingle_blocks.1.modulation.lin.weight=1.0\nsingle_blocks.1.modulation.lin.bias=1.0\nsingle_blocks.2.linear1.weight=1.0\nsingle_blocks.2.linear1.bias=1.0\nsingle_blocks.2.linear2.weight=1.0\nsingle_blocks.2.linear2.bias=1.0\nsingle_blocks.2.modulation.lin.weight=1.0\nsingle_blocks.2.modulation.lin.bias=1.0\nsingle_blocks.3.linear1.weight=1.0\nsingle_blocks.3.linear1.bias=1.0\nsingle_blocks.3.linear2.weight=1.0\nsingle_blocks.3.linear2.bias=1.0\nsingle_blocks.3.modulation.lin.weight=1.0\nsingle_blocks.3.modulation.lin.bias=1.0\nsingle_blocks.4.linear1.weight=1.0\nsingle_blocks.4.linear1.bias=1.0\nsingle_blocks.4.linear2.weight=1.0\nsingle_blocks.4.linear2.bias=1.0\nsingle_blocks.4.modulation.lin.weight=1.0\nsingle_blocks.4.modulation.lin.bias=1.0\nsingle_blocks.5.linear1.weight=1.0\nsingle_blocks.5.linear1.bias=1.0\nsingle_blocks.5.linear2.weight=1.0\nsingle_blocks.5.linear2.bias=1.0\nsingle_blocks.5.modulation.lin.weight=1.0\nsingle_blocks.5.modulation.lin.bias=1.0\nsingle_blocks.6.linear1.weight=1.0\nsingle_blocks.6.linear1.bias=1.0\nsingle_blocks.6.linear2.weight=1.0\nsingle_blocks.6.linear2.bias=1.0\nsingle_blocks.6.modulation.lin.weight=1.0\nsingle_blocks.6.modulation.lin.bias=1.0\nsingle_blocks.7.linear1.weight=1.0\nsingle_blocks.7.linear1.bias=1.0\nsingle_blocks.7.linear2.weight=1.0\nsingle_blocks.7.linear2.bias=1.0\nsingle_blocks.7.modulation.lin.weight=1.0\nsingle_blocks.7.modulation.lin.bias=1.0\nsingle_blocks.8.linear1.weight=1.0\nsingle_blocks.8.linear1.bias=1.0\nsingle_blocks.8.linear2.weight=1.0\nsingle_blocks.8.linear2.bias=1.0\nsingle_blocks.8.modulation.lin.weight=1.0\nsingle_blocks.8.modulation.lin.bias=1.0\nsingle_blocks.9.linear1.weight=1.0\nsingle_blocks.9.linear1.bias=1.0\nsingle_blocks.9.linear2.weight=1.0\nsingle_blocks.9.linear2.bias=1.0\nsingle_blocks.9.modulation.lin.weight=1.0\nsingle_blocks.9.modulation.lin.bias=1.0\nsingle_blocks.10.linear1.weight=1.0\nsingle_blocks.10.linear1.bias=1.0\nsingle_blocks.10.linear2.weight=1.0\nsingle_blocks.10.linear2.bias=1.0\nsingle_blocks.10.modulation.lin.weight=1.0\nsingle_blocks.10.modulation.lin.bias=1.0\nsingle_blocks.11.linear1.weight=1.0\nsingle_blocks.11.linear1.bias=1.0\nsingle_blocks.11.linear2.weight=1.0\nsingle_blocks.11.linear2.bias=1.0\nsingle_blocks.11.modulation.lin.weight=1.0\nsingle_blocks.11.modulation.lin.bias=1.0\nsingle_blocks.12.linear1.weight=1.0\nsingle_blocks.12.linear1.bias=1.0\nsingle_blocks.12.linear2.weight=1.0\nsingle_blocks.12.linear2.bias=1.0\nsingle_blocks.12.modulation.lin.weight=1.0\nsingle_blocks.12.modulation.lin.bias=1.0\nsingle_blocks.13.linear1.weight=1.0\nsingle_blocks.13.linear1.bias=1.0\nsingle_blocks.13.linear2.weight=1.0\nsingle_blocks.13.linear2.bias=1.0\nsingle_blocks.13.modulation.lin.weight=1.0\nsingle_blocks.13.modulation.lin.bias=1.0\nsingle_blocks.14.linear1.weight=1.0\nsingle_blocks.14.linear1.bias=1.0\nsingle_blocks.14.linear2.weight=1.0\nsingle_blocks.14.linear2.bias=1.0\nsingle_blocks.14.modulation.lin.weight=1.0\nsingle_blocks.14.modulation.lin.bias=1.0\nsingle_blocks.15.linear1.weight=1.0\nsingle_blocks.15.linear1.bias=1.0\nsingle_blocks.15.linear2.weight=1.0\nsingle_blocks.15.linear2.bias=1.0\nsingle_blocks.15.modulation.lin.weight=1.0\nsingle_blocks.15.modulation.lin.bias=1.0\nsingle_blocks.16.linear1.weight=1.0\nsingle_blocks.16.linear1.bias=1.0\nsingle_blocks.16.linear2.weight=1.0\nsingle_blocks.16.linear2.bias=1.0\nsingle_blocks.16.modulation.lin.weight=1.0\nsingle_blocks.16.modulation.lin.bias=1.0\nsingle_blocks.17.linear1.weight=1.0\nsingle_blocks.17.linear1.bias=1.0\nsingle_blocks.17.linear2.weight=1.0\nsingle_blocks.17.linear2.bias=1.0\nsingle_blocks.17.modulation.lin.weight=1.0\nsingle_blocks.17.modulation.lin.bias=1.0\nsingle_blocks.18.linear1.weight=1.0\nsingle_blocks.18.linear1.bias=1.0\nsingle_blocks.18.linear2.weight=1.0\nsingle_blocks.18.linear2.bias=1.0\nsingle_blocks.18.modulation.lin.weight=1.0\nsingle_blocks.18.modulation.lin.bias=1.0\nsingle_blocks.19.linear1.weight=1.0\nsingle_blocks.19.linear1.bias=1.0\nsingle_blocks.19.linear2.weight=1.0\nsingle_blocks.19.linear2.bias=1.0\nsingle_blocks.19.modulation.lin.weight=1.0\nsingle_blocks.19.modulation.lin.bias=1.0\nsingle_blocks.20.linear1.weight=1.0\nsingle_blocks.20.linear1.bias=1.0\nsingle_blocks.20.linear2.weight=1.0\nsingle_blocks.20.linear2.bias=1.0\nsingle_blocks.20.modulation.lin.weight=1.0\nsingle_blocks.20.modulation.lin.bias=1.0\nsingle_blocks.21.linear1.weight=1.0\nsingle_blocks.21.linear1.bias=1.0\nsingle_blocks.21.linear2.weight=1.0\nsingle_blocks.21.linear2.bias=1.0\nsingle_blocks.21.modulation.lin.weight=1.0\nsingle_blocks.21.modulation.lin.bias=1.0\nsingle_blocks.22.linear1.weight=1.0\nsingle_blocks.22.linear1.bias=1.0\nsingle_blocks.22.linear2.weight=1.0\nsingle_blocks.22.linear2.bias=1.0\nsingle_blocks.22.modulation.lin.weight=1.0\nsingle_blocks.22.modulation.lin.bias=1.0\nsingle_blocks.23.linear1.weight=1.0\nsingle_blocks.23.linear1.bias=1.0\nsingle_blocks.23.linear2.weight=1.0\nsingle_blocks.23.linear2.bias=1.0\nsingle_blocks.23.modulation.lin.weight=1.0\nsingle_blocks.23.modulation.lin.bias=1.0\nsingle_blocks.24.linear1.weight=1.0\nsingle_blocks.24.linear1.bias=1.0\nsingle_blocks.24.linear2.weight=1.0\nsingle_blocks.24.linear2.bias=1.0\nsingle_blocks.24.modulation.lin.weight=1.0\nsingle_blocks.24.modulation.lin.bias=1.0\nsingle_blocks.25.linear1.weight=1.0\nsingle_blocks.25.linear1.bias=1.0\nsingle_blocks.25.linear2.weight=1.0\nsingle_blocks.25.linear2.bias=1.0\nsingle_blocks.25.modulation.lin.weight=1.0\nsingle_blocks.25.modulation.lin.bias=1.0\nsingle_blocks.26.linear1.weight=1.0\nsingle_blocks.26.linear1.bias=1.0\nsingle_blocks.26.linear2.weight=1.0\nsingle_blocks.26.linear2.bias=1.0\nsingle_blocks.26.modulation.lin.weight=1.0\nsingle_blocks.26.modulation.lin.bias=1.0\nsingle_blocks.27.linear1.weight=1.0\nsingle_blocks.27.linear1.bias=1.0\nsingle_blocks.27.linear2.weight=1.0\nsingle_blocks.27.linear2.bias=1.0\nsingle_blocks.27.modulation.lin.weight=1.0\nsingle_blocks.27.modulation.lin.bias=1.0\nsingle_blocks.28.linear1.weight=1.0\nsingle_blocks.28.linear1.bias=1.0\nsingle_blocks.28.linear2.weight=1.0\nsingle_blocks.28.linear2.bias=1.0\nsingle_blocks.28.modulation.lin.weight=1.0\nsingle_blocks.28.modulation.lin.bias=1.0\nsingle_blocks.29.linear1.weight=1.0\nsingle_blocks.29.linear1.bias=1.0\nsingle_blocks.29.linear2.weight=1.0\nsingle_blocks.29.linear2.bias=1.0\nsingle_blocks.29.modulation.lin.weight=1.0\nsingle_blocks.29.modulation.lin.bias=1.0\nsingle_blocks.30.linear1.weight=1.0\nsingle_blocks.30.linear1.bias=1.0\nsingle_blocks.30.linear2.weight=1.0\nsingle_blocks.30.linear2.bias=1.0\nsingle_blocks.30.modulation.lin.weight=1.0\nsingle_blocks.30.modulation.lin.bias=1.0\nsingle_blocks.31.linear1.weight=1.0\nsingle_blocks.31.linear1.bias=1.0\nsingle_blocks.31.linear2.weight=1.0\nsingle_blocks.31.linear2.bias=1.0\nsingle_blocks.31.modulation.lin.weight=1.0\nsingle_blocks.31.modulation.lin.bias=1.0\nsingle_blocks.32.linear1.weight=1.0\nsingle_blocks.32.linear1.bias=1.0\nsingle_blocks.32.linear2.weight=1.0\nsingle_blocks.32.linear2.bias=1.0\nsingle_blocks.32.modulation.lin.weight=1.0\nsingle_blocks.32.modulation.lin.bias=1.0\nsingle_blocks.33.linear1.weight=1.0\nsingle_blocks.33.linear1.bias=1.0\nsingle_blocks.33.linear2.weight=1.0\nsingle_blocks.33.linear2.bias=1.0\nsingle_blocks.33.modulation.lin.weight=1.0\nsingle_blocks.33.modulation.lin.bias=1.0\nsingle_blocks.34.linear1.weight=1.0\nsingle_blocks.34.linear1.bias=1.0\nsingle_blocks.34.linear2.weight=1.0\nsingle_blocks.34.linear2.bias=1.0\nsingle_blocks.34.modulation.lin.weight=1.0\nsingle_blocks.34.modulation.lin.bias=1.0\nsingle_blocks.35.linear1.weight=1.0\nsingle_blocks.35.linear1.bias=1.0\nsingle_blocks.35.linear2.weight=1.0\nsingle_blocks.35.linear2.bias=1.0\nsingle_blocks.35.modulation.lin.weight=1.0\nsingle_blocks.35.modulation.lin.bias=1.0\nsingle_blocks.36.linear1.weight=1.0\nsingle_blocks.36.linear1.bias=1.0\nsingle_blocks.36.linear2.weight=1.0\nsingle_blocks.36.linear2.bias=1.0\nsingle_blocks.36.modulation.lin.weight=1.0\nsingle_blocks.36.modulation.lin.bias=1.0\nsingle_blocks.37.linear1.weight=1.0\nsingle_blocks.37.linear1.bias=1.0\nsingle_blocks.37.linear2.weight=1.0\nsingle_blocks.37.linear2.bias=1.0\nsingle_blocks.37.modulation.lin.weight=1.0\nsingle_blocks.37.modulation.lin.bias",
        "flux_model_layers_value": 1.01,
        "flux_model_layers_to_patch": "all",
        "weights_and_biases_to_patch": "weights and biases",
        "flux_model_layers_regular_expressions": []
    }
)
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 fofr/sandbox 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": "fofr/sandbox:f68003314c9da95a133e95cea39a81e92a4e4b724ce57ac2efd29ec196f49e6d",
    "input": {
      "max_shift": 1.15,
      "base_shift": 0.5,
      "num_outputs": 1,
      "aspect_ratio": "1:1",
      "output_format": "webp",
      "guidance_scale": 3,
      "output_quality": 95,
      "num_inference_steps": 28,
      "flux_layers_to_patch": 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      "flux_model_layers_value": 1.01,
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      "weights_and_biases_to_patch": "weights and biases",
      "flux_model_layers_regular_expressions": []
    }
  }' \
  https://api.replicate.com/v1/predictions

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