lucataco/flux-schnell-lora:2a6b576a – Run with an API on Replicate

Version

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lucataco /flux-schnell-lora:2a6b576a

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: "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 (or denoising strength) when using image to image. 1.0 corresponds to full destruction of information in image.

Default: 0.8

num_outputs

integer

(minimum: 1, maximum: 4)

Number of images to output.

Default: 1

num_inference_steps

integer

(minimum: 1, maximum: 12)

Number of inference steps

Default: 4

seed

integer

Random seed. Set for reproducible generation

hf_lora

string

Shift + Return to add a new line

Huggingface path, or URL to the LoRA weights. Ex: alvdansen/frosting_lane_flux

lora_scale

number

(minimum: 0, maximum: 1)

Scale for the LoRA weights

Default: 0.8

Including output_format and 2 more...

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

npx create-replicate --model=lucataco/flux-schnell-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";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run lucataco/flux-schnell-lora using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "lucataco/flux-schnell-lora:2a6b576af31790b470f0a8442e1e9791213fa13799cbb65a9fc1436e96389574",
  {
    input: {
      lora_scale: 0.8,
      num_outputs: 1,
      aspect_ratio: "1:1",
      output_format: "webp",
      output_quality: 80,
      prompt_strength: 0.8,
      num_inference_steps: 4
    }
  }
);
console.log(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 lucataco/flux-schnell-lora using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "lucataco/flux-schnell-lora:2a6b576af31790b470f0a8442e1e9791213fa13799cbb65a9fc1436e96389574",
    input={
        "lora_scale": 0.8,
        "num_outputs": 1,
        "aspect_ratio": "1:1",
        "output_format": "webp",
        "output_quality": 80,
        "prompt_strength": 0.8,
        "num_inference_steps": 4
    }
)
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 lucataco/flux-schnell-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": "2a6b576af31790b470f0a8442e1e9791213fa13799cbb65a9fc1436e96389574",
    "input": {
      "lora_scale": 0.8,
      "num_outputs": 1,
      "aspect_ratio": "1:1",
      "output_format": "webp",
      "output_quality": 80,
      "prompt_strength": 0.8,
      "num_inference_steps": 4
    }
  }' \
  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.