Prediction

Model

lucataco/flux-schnell-lora:2a6b576a

x9jxf1dv7nrj20chs7jvaprbng

Status

Succeeded

Source

Web

Hardware

A100 (80GB)

Total duration

2.8s

Created

over 1 year ago by lucataco

Webhook

–

Input

prompt: a beautiful castle frstingln illustration
aspect_ratio: 1:1
prompt_strength: 0.8
num_outputs: 1
num_inference_steps: 4
output_format: webp
output_quality: 80
hf_lora: alvdansen/frosting_lane_flux
lora_scale: 0.8

{
  "aspect_ratio": "1:1",
  "hf_lora": "alvdansen/frosting_lane_flux",
  "lora_scale": 0.8,
  "num_inference_steps": 4,
  "num_outputs": 1,
  "output_format": "webp",
  "output_quality": 80,
  "prompt": "a beautiful castle frstingln illustration",
  "prompt_strength": 0.8
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_DnB**********************************

This is your API token. Keep it to yourself.

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 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: {
      aspect_ratio: "1:1",
      hf_lora: "alvdansen/frosting_lane_flux",
      lora_scale: 0.8,
      num_inference_steps: 4,
      num_outputs: 1,
      output_format: "webp",
      output_quality: 80,
      prompt: "a beautiful castle frstingln illustration",
      prompt_strength: 0.8
    }
  }
);

// 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=r8_DnB**********************************

This is your API token. Keep it to yourself.

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={
        "aspect_ratio": "1:1",
        "hf_lora": "alvdansen/frosting_lane_flux",
        "lora_scale": 0.8,
        "num_inference_steps": 4,
        "num_outputs": 1,
        "output_format": "webp",
        "output_quality": 80,
        "prompt": "a beautiful castle frstingln illustration",
        "prompt_strength": 0.8
    }
)

# 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=r8_DnB**********************************

This is your API token. Keep it to yourself.

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": "lucataco/flux-schnell-lora:2a6b576af31790b470f0a8442e1e9791213fa13799cbb65a9fc1436e96389574",
    "input": {
      "aspect_ratio": "1:1",
      "hf_lora": "alvdansen/frosting_lane_flux",
      "lora_scale": 0.8,
      "num_inference_steps": 4,
      "num_outputs": 1,
      "output_format": "webp",
      "output_quality": 80,
      "prompt": "a beautiful castle frstingln illustration",
      "prompt_strength": 0.8
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

2.7 seconds

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