lightweight-ai/model2:1246c90e – Run with an API on Replicate

Version

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lightweight-ai /model2:1246c90e

Input

prompt

string

Shift + Return to add a new line

A fluffy, orange tabby cat curled up asleep in a sunbeam streaming through a window, its soft fur glowing with the warmth of the light; highly detailed 8K UHD photorealistic rendering, natural lighting, warm and inviting atmosphere, focus on softness and texture.A fluffy, orange tabby cat curled up asleep in a sunbeam streaming through a window, its soft fur glowing with the warmth of the light; highly detailed 8K UHD photorealistic rendering, natural lighting, warm and inviting atmosphere, focus on softness and texture.

Prompt for generated image

Default: "A fluffy, orange tabby cat curled up asleep in a sunbeam streaming through a window, its soft fur glowing with the warmth of the light; highly detailed 8K UHD photorealistic rendering, natural lighting, warm and inviting atmosphere, focus on softness and texture."

image

string

Shift + Return to add a new line

image url

width

integer

Width of output image

Default: 1024

height

integer

Height of output image

Default: 1024

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: 50)

Number of inference steps

Default: 28

loras

*string[]

Lora list

lora_scales

*number[]

Enter a string of numbers separated by commas

Lora scales

seed

integer

Random seed. Set for reproducible generation

output_format

string

Format of the output images

Default: "png"

output_quality

integer

(minimum: 0, 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: 100

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

npx create-replicate --model=lightweight-ai/model2

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 lightweight-ai/model2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "lightweight-ai/model2:1246c90e8d3af59d466924a1221ec6cd7183b5e88659be2ccdc106a979b3f69a",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "A fluffy, orange tabby cat curled up asleep in a sunbeam streaming through a window, its soft fur glowing with the warmth of the light; highly detailed 8K UHD photorealistic rendering, natural lighting, warm and inviting atmosphere, focus on softness and texture.",
      num_outputs: 1,
      output_format: "png",
      output_quality: 100,
      prompt_strength: 0.8,
      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 lightweight-ai/model2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "lightweight-ai/model2:1246c90e8d3af59d466924a1221ec6cd7183b5e88659be2ccdc106a979b3f69a",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "A fluffy, orange tabby cat curled up asleep in a sunbeam streaming through a window, its soft fur glowing with the warmth of the light; highly detailed 8K UHD photorealistic rendering, natural lighting, warm and inviting atmosphere, focus on softness and texture.",
        "num_outputs": 1,
        "output_format": "png",
        "output_quality": 100,
        "prompt_strength": 0.8,
        "num_inference_steps": 28
    }
)
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 lightweight-ai/model2 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": "1246c90e8d3af59d466924a1221ec6cd7183b5e88659be2ccdc106a979b3f69a",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "A fluffy, orange tabby cat curled up asleep in a sunbeam streaming through a window, its soft fur glowing with the warmth of the light; highly detailed 8K UHD photorealistic rendering, natural lighting, warm and inviting atmosphere, focus on softness and texture.",
      "num_outputs": 1,
      "output_format": "png",
      "output_quality": 100,
      "prompt_strength": 0.8,
      "num_inference_steps": 28
    }
  }' \
  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.