Prediction

Model

prunaai/sdxl-lightning:123d4264

s95hh10fvhrj40cqbdgaag8nac

Status

Succeeded

Source

Web

Hardware

A100 (80GB)

Total duration

0.4s

Created

6 months ago

Webhook

–

Input

prompt: self-portrait of a woman, lightning in the background
num_images: 1
num_inference_steps: 4
guidance_scale: 0
seed: 42
image_height: 1024
image_width: 1024
output_format: jpg
output_quality: 80

{
  "guidance_scale": 0,
  "image_height": 1024,
  "image_width": 1024,
  "num_images": 1,
  "num_inference_steps": 4,
  "output_format": "jpg",
  "output_quality": 80,
  "prompt": "self-portrait of a woman, lightning in the background",
  "seed": 42
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_RYu**********************************

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 prunaai/sdxl-lightning using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "prunaai/sdxl-lightning:123d4264aec4d1c81d8bf142e0d90d6fd4c346f1a869406019f6d1653882d7c3",
  {
    input: {
      guidance_scale: 0,
      image_height: 1024,
      image_width: 1024,
      num_images: 1,
      num_inference_steps: 4,
      output_format: "jpg",
      output_quality: 80,
      prompt: "self-portrait of a woman, lightning in the background",
      seed: 42
    }
  }
);

// To access the file URL:
console.log(output.url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", 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=r8_RYu**********************************

This is your API token. Keep it to yourself.

Import the client:

import replicate

Run prunaai/sdxl-lightning using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "prunaai/sdxl-lightning:123d4264aec4d1c81d8bf142e0d90d6fd4c346f1a869406019f6d1653882d7c3",
    input={
        "guidance_scale": 0,
        "image_height": 1024,
        "image_width": 1024,
        "num_images": 1,
        "num_inference_steps": 4,
        "output_format": "jpg",
        "output_quality": 80,
        "prompt": "self-portrait of a woman, lightning in the background",
        "seed": 42
    }
)

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

# To write the file to disk:
with open("my-image.png", "wb") as file:
    file.write(output.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_RYu**********************************

This is your API token. Keep it to yourself.

Run prunaai/sdxl-lightning 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/sdxl-lightning:123d4264aec4d1c81d8bf142e0d90d6fd4c346f1a869406019f6d1653882d7c3",
    "input": {
      "guidance_scale": 0,
      "image_height": 1024,
      "image_width": 1024,
      "num_images": 1,
      "num_inference_steps": 4,
      "output_format": "jpg",
      "output_quality": 80,
      "prompt": "self-portrait of a woman, lightning in the background",
      "seed": 42
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

0.4 seconds

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