mgonline2021/sdxlorarlvsn – Run with an API on Replicate

mgonline2021 / sdxlorarlvsn

Cold

Public
127 runs
8x L40S

Iterate in playground

Run with an API

Playground API Examples README Versions

Input

num_samples

integer

(minimum: 1, maximum: 4)

num_samples

Default: 1

pose_image

*file

Pose image

pose_resemblance

number

(minimum: 0, maximum: 1)

Control Guidance End (0 - 1)

Default: 0.8

face_image

*file

Face image

face_resemblance

number

(minimum: 0, maximum: 1)

Face Conditioning Scale (0 - 1)

Default: 0.5

face_expanding_bbox

number

(minimum: 0, maximum: 1)

Face Expanding bbox (0 - 1)

Default: 0.5

prompt

string

Shift + Return to add a new line

a portrait of a [MODEL] with a suit and a tiea portrait of a [MODEL] with a suit and a tie

Default: "a portrait of a [MODEL] with a suit and a tie"

n_prompt

string

Shift + Return to add a new line

Default: ""

steps

integer

(minimum: 0, maximum: 50)

num_inference_steps

Default: 8

width

integer

Width

Default: 768

seed

integer

(minimum: 0, maximum: 2147483647)

Seed (0 = random, maximum: 2147483647)

Default: 0

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

npx create-replicate --model=mgonline2021/sdxlorarlvsn

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 mgonline2021/sdxlorarlvsn using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "mgonline2021/sdxlorarlvsn:910b08b1804e83d83675f1da6a4e94bcafe4aec951c9414fb47fddd6a38ef3c3",
  {
    input: {
      seed: 0,
      steps: 8,
      width: 768,
      prompt: "a portrait of a [MODEL] with a suit and a tie",
      n_prompt: "",
      num_samples: 1,
      face_resemblance: 0.5,
      pose_resemblance: 0.8,
      face_expanding_bbox: 0.5
    }
  }
);

// 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 mgonline2021/sdxlorarlvsn using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "mgonline2021/sdxlorarlvsn:910b08b1804e83d83675f1da6a4e94bcafe4aec951c9414fb47fddd6a38ef3c3",
    input={
        "seed": 0,
        "steps": 8,
        "width": 768,
        "prompt": "a portrait of a [MODEL] with a suit and a tie",
        "n_prompt": "",
        "num_samples": 1,
        "face_resemblance": 0.5,
        "pose_resemblance": 0.8,
        "face_expanding_bbox": 0.5
    }
)
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 mgonline2021/sdxlorarlvsn 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": "mgonline2021/sdxlorarlvsn:910b08b1804e83d83675f1da6a4e94bcafe4aec951c9414fb47fddd6a38ef3c3",
    "input": {
      "seed": 0,
      "steps": 8,
      "width": 768,
      "prompt": "a portrait of a [MODEL] with a suit and a tie",
      "n_prompt": "",
      "num_samples": 1,
      "face_resemblance": 0.5,
      "pose_resemblance": 0.8,
      "face_expanding_bbox": 0.5
    }
  }' \
  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.

Run time and cost

This model costs approximately $0.32 to run on Replicate, or 3 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker.

This model runs on 8x Nvidia L40S GPU hardware. Predictions typically complete within 42 seconds. The predict time for this model varies significantly based on the inputs.

Readme

This model doesn't have a readme.