camenduru/lgm:b1be9ed2 – Run with an API on Replicate

Version

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camenduru /lgm:b1be9ed2

Playground API

Input

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

npx create-replicate --model=camenduru/lgm

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

const output = await replicate.run(
  "camenduru/lgm:b1be9ed23fa0b30e01a13179f6ace55dbbfc16f6d11072e1d37971ab46c6fd1e",
  {
    input: {
      seed: 42,
      prompt: "a person facing the camera, making a hand gesture, indoor",
      negative_prompt: "ugly, blurry, pixelated obscure, unnatural colors, poor lighting, dull, unclear, cropped, lowres, low quality, artifacts, duplicate"
    }
  }
);
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 camenduru/lgm using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "camenduru/lgm:b1be9ed23fa0b30e01a13179f6ace55dbbfc16f6d11072e1d37971ab46c6fd1e",
    input={
        "seed": 42,
        "prompt": "a person facing the camera, making a hand gesture, indoor",
        "negative_prompt": "ugly, blurry, pixelated obscure, unnatural colors, poor lighting, dull, unclear, cropped, lowres, low quality, artifacts, duplicate"
    }
)
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 camenduru/lgm 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": "b1be9ed23fa0b30e01a13179f6ace55dbbfc16f6d11072e1d37971ab46c6fd1e",
    "input": {
      "seed": 42,
      "prompt": "a person facing the camera, making a hand gesture, indoor",
      "negative_prompt": "ugly, blurry, pixelated obscure, unnatural colors, poor lighting, dull, unclear, cropped, lowres, low quality, artifacts, duplicate"
    }
  }' \
  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/camenduru/lgm@sha256:b1be9ed23fa0b30e01a13179f6ace55dbbfc16f6d11072e1d37971ab46c6fd1e \
  -i 'seed=42' \
  -i 'prompt="a person facing the camera, making a hand gesture, indoor"' \
  -i 'negative_prompt="ugly, blurry, pixelated obscure, unnatural colors, poor lighting, dull, unclear, cropped, lowres, low quality, artifacts, duplicate"'

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 r8.im/camenduru/lgm@sha256:b1be9ed23fa0b30e01a13179f6ace55dbbfc16f6d11072e1d37971ab46c6fd1e
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "seed": 42,
      "prompt": "a person facing the camera, making a hand gesture, indoor",
      "negative_prompt": "ugly, blurry, pixelated obscure, unnatural colors, poor lighting, dull, unclear, cropped, lowres, low quality, artifacts, duplicate"
    }
  }' \
  http://localhost:5000/predictions

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

Output

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