prunaai/flux.1-dev-lora | Run with an API on Replicate

prunaai / flux.1-dev-lora

This is a 3x faster FLUX.1 [dev] model from Black Forest Labs, optimised with pruna with minimal quality loss.

Cold

Public
659 runs
H100
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Iterate in playground

Run with an API

Playground API Examples README Versions

Input

prompt

*string

Shift + Return to add a new line

Long toons, a close-up of a cartoon characters face is featured in a vibrant red backdrop. The characters head is adorned with a gray hoodie, a red t-shirt, and a pair of pink earbuds. His eyes, a nose, and mustache are adorned with tiny white dots, adding a pop of color to the scene. His hair is a mix of black and gray, while his ears are a darker shade of pink.Long toons, a close-up of a cartoon characters face is featured in a vibrant red backdrop. The characters head is adorned with a gray hoodie, a red t-shirt, and a pair of pink earbuds. His eyes, a nose, and mustache are adorned with tiny white dots, adding a pop of color to the scene. His hair is a mix of black and gray, while his ears are a darker shade of pink.

Prompt for generated image

aspect_ratio

string

Aspect ratio of the output image

Default: "1:1"

image

file

Input image for image to image mode. The aspect ratio of your output will match this image

prompt_strength

number

(minimum: 0, maximum: 1)

Prompt strength when using img2img. 1.0 corresponds to full destruction of information in image

Default: 0.8

num_outputs

integer

(minimum: 1, maximum: 4)

Number of outputs to generate

Default: 1

num_inference_steps

integer

Number of denoising steps. Recommended range is 28-50, and lower number of steps produce lower quality outputs, faster.

Default: 28

guidance

number

(minimum: 0, maximum: 10)

Guidance for generated image

Default: 3

seed

integer

Random seed. Set for reproducible generation

output_format

string

Format of the output images

Default: "jpg"

output_quality

integer

(minimum: 1, 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

speed_mode

string

Speed optimization level

Default: "Juiced 🧃"

lora

string

Shift + Return to add a new line

Load LoRA weights. Supports HuggingFace URLs in the format <owner>/<model-name>[/<lora-weights-file.safetensors>]. For example, 'fofr/flux-pixar-cars'.

lora_scale

number

(minimum: -1, maximum: 3)

Determines how strongly the main LoRA should be applied. Sane results between 0 and 1 for base inference. For go_fast we apply a 1.5x multiplier to this value; we've generally seen good performance when scaling the base value by that amount. You may still need to experiment to find the best value for your particular lora.

Default: 1

extra_lora

string

Shift + Return to add a new line

Load LoRA weights. Supports HuggingFace URLs in the format <owner>/<model-name>[/<lora-weights-file.safetensors>]. For example, 'fofr/flux-pixar-cars'.

extra_lora_scale

number

(minimum: -1, maximum: 3)

Determines how strongly the extra LoRA should be applied. Sane results between 0 and 1 for base inference. For go_fast we apply a 1.5x multiplier to this value; we've generally seen good performance when scaling the base value by that amount. You may still need to experiment to find the best value for your particular lora.

Default: 1

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=prunaai/flux.1-dev-lora

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-dev-lora 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-dev-lora:19048f659cedeb72d7bbf6a3c4ee8fc79998e2c3b440ba489b44ac028489e8b1",
  {
    input: {
      lora: "prithivMLmods/Flux-Long-Toon-LoRA",
      seed: 0,
      prompt: "Long toons, a close-up of a cartoon characters face is featured in a vibrant red backdrop. The characters head is adorned with a gray hoodie, a red t-shirt, and a pair of pink earbuds. His eyes, a nose, and mustache are adorned with tiny white dots, adding a pop of color to the scene. His hair is a mix of black and gray, while his ears are a darker shade of pink.",
      guidance: 3,
      lora_scale: 1,
      megapixels: "1",
      speed_mode: "Extra Juiced 🔥",
      num_outputs: 1,
      aspect_ratio: "1:1",
      output_format: "jpg",
      output_quality: 80,
      prompt_strength: 0.8,
      extra_lora_scale: 1,
      num_inference_steps: 28
    }
  }
);

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

output = replicate.run(
    "prunaai/flux.1-dev-lora:19048f659cedeb72d7bbf6a3c4ee8fc79998e2c3b440ba489b44ac028489e8b1",
    input={
        "lora": "prithivMLmods/Flux-Long-Toon-LoRA",
        "seed": 0,
        "prompt": "Long toons, a close-up of a cartoon characters face is featured in a vibrant red backdrop. The characters head is adorned with a gray hoodie, a red t-shirt, and a pair of pink earbuds. His eyes, a nose, and mustache are adorned with tiny white dots, adding a pop of color to the scene. His hair is a mix of black and gray, while his ears are a darker shade of pink.",
        "guidance": 3,
        "lora_scale": 1,
        "megapixels": "1",
        "speed_mode": "Extra Juiced 🔥",
        "num_outputs": 1,
        "aspect_ratio": "1:1",
        "output_format": "jpg",
        "output_quality": 80,
        "prompt_strength": 0.8,
        "extra_lora_scale": 1,
        "num_inference_steps": 28
    }
)

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

# To write the file to disk:
with open("my-image.png", "wb") as file:
    file.write(output[0].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-dev-lora 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-dev-lora:19048f659cedeb72d7bbf6a3c4ee8fc79998e2c3b440ba489b44ac028489e8b1",
    "input": {
      "lora": "prithivMLmods/Flux-Long-Toon-LoRA",
      "seed": 0,
      "prompt": "Long toons, a close-up of a cartoon characters face is featured in a vibrant red backdrop. The characters head is adorned with a gray hoodie, a red t-shirt, and a pair of pink earbuds. His eyes, a nose, and mustache are adorned with tiny white dots, adding a pop of color to the scene. His hair is a mix of black and gray, while his ears are a darker shade of pink.",
      "guidance": 3,
      "lora_scale": 1,
      "megapixels": "1",
      "speed_mode": "Extra Juiced 🔥",
      "num_outputs": 1,
      "aspect_ratio": "1:1",
      "output_format": "jpg",
      "output_quality": 80,
      "prompt_strength": 0.8,
      "extra_lora_scale": 1,
      "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

2.1 seconds

Tweak it ShareReport View full prediction

Examples

View more examples

Run time and cost

This model costs approximately $1.25 to run on Replicate, or 0 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 14 minutes.