lightweight-ai/lwjay – Run with an API on Replicate

lightweight-ai / lwjay

Cold

Public
0 runs
L40S

Run with an API

Playground API Examples README Versions

Input

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

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

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

const output = await replicate.run(
  "lightweight-ai/lwjay:136ff73f6b79a6b7a659bf923aceb7be43015905fff83eee29559f496c87e365",
  {
    input: {
      width: 1280,
      height: 1024,
      prompt: "High quailty, 4K, UHD",
      guidance: 30,
      alignment: "Middle",
      overlap_top: true,
      overlap_left: true,
      overlap_right: true,
      resize_option: "Full",
      overlap_bottom: true,
      overlap_percentage: 10,
      num_inference_steps: 28,
      custom_resize_percentage: 50
    }
  }
);

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

output = replicate.run(
    "lightweight-ai/lwjay:136ff73f6b79a6b7a659bf923aceb7be43015905fff83eee29559f496c87e365",
    input={
        "width": 1280,
        "height": 1024,
        "prompt": "High quailty, 4K, UHD",
        "guidance": 30,
        "alignment": "Middle",
        "overlap_top": True,
        "overlap_left": True,
        "overlap_right": True,
        "resize_option": "Full",
        "overlap_bottom": True,
        "overlap_percentage": 10,
        "num_inference_steps": 28,
        "custom_resize_percentage": 50
    }
)
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/lwjay 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": "136ff73f6b79a6b7a659bf923aceb7be43015905fff83eee29559f496c87e365",
    "input": {
      "width": 1280,
      "height": 1024,
      "prompt": "High quailty, 4K, UHD",
      "guidance": 30,
      "alignment": "Middle",
      "overlap_top": true,
      "overlap_left": true,
      "overlap_right": true,
      "resize_option": "Full",
      "overlap_bottom": true,
      "overlap_percentage": 10,
      "num_inference_steps": 28,
      "custom_resize_percentage": 50
    }
  }' \
  https://api.replicate.com/v1/predictions

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

You can run this model locally using Cog. First, install Cog:

brew install cog

If you don’t have Homebrew, there are other installation options available.

Run this to download the model and run it in your local environment:

cog predict r8.im/lightweight-ai/lwjay@sha256:136ff73f6b79a6b7a659bf923aceb7be43015905fff83eee29559f496c87e365 \
  -i 'width=1280' \
  -i 'height=1024' \
  -i 'prompt="High quailty, 4K, UHD"' \
  -i 'guidance=30' \
  -i 'alignment="Middle"' \
  -i 'overlap_top=true' \
  -i 'overlap_left=true' \
  -i 'overlap_right=true' \
  -i 'resize_option="Full"' \
  -i 'overlap_bottom=true' \
  -i 'overlap_percentage=10' \
  -i 'num_inference_steps=28' \
  -i 'custom_resize_percentage=50'

To learn more, take a look at the Cog documentation.

Run this to download the model and run it in your local environment:

docker run -d -p 5000:5000 --gpus=all r8.im/lightweight-ai/lwjay@sha256:136ff73f6b79a6b7a659bf923aceb7be43015905fff83eee29559f496c87e365
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "width": 1280,
      "height": 1024,
      "prompt": "High quailty, 4K, UHD",
      "guidance": 30,
      "alignment": "Middle",
      "overlap_top": true,
      "overlap_left": true,
      "overlap_right": true,
      "resize_option": "Full",
      "overlap_bottom": true,
      "overlap_percentage": 10,
      "num_inference_steps": 28,
      "custom_resize_percentage": 50
    }
  }' \
  http://localhost:5000/predictions

To learn more, take a look at the Cog documentation.

Output

No output yet! Press "Submit" to start a prediction.

Run time and cost

This model runs on Nvidia L40S GPU hardware. We don't yet have enough runs of this model to provide performance information.

Readme

This model doesn't have a readme.