camenduru/renoise-inversion:c21e3ec4 – Run with an API on Replicate

Version

You're looking at a specific version of this model. Jump to the model overview.

camenduru /renoise-inversion:c21e3ec4

Playground API

Input

Input_Image

*file

Input Image

Source_Prompt

string

Shift + Return to add a new line

A kitten is sitting in a basket on a branchA kitten is sitting in a basket on a branch

Default: "A kitten is sitting in a basket on a branch"

Target_Prompt

string

Shift + Return to add a new line

a lego kitten is sitting in a basket on a brancha lego kitten is sitting in a basket on a branch

Default: "a lego kitten is sitting in a basket on a branch"

Denoise_Classifier_Free_Guidence_Scale

number

Default: 1

Number_of_ReNoise_Iterations

integer

Default: 9

Inversion_Strength

number

Default: 1

Preform_Estimation_Averaging

boolean

Default: true

First_Estimation_in_Average_T_L

integer

Default: 0

Last_Estimation_in_Average_T_L

integer

Default: 5

First_Estimation_in_Average_T_G

integer

Default: 8

Last_Estimation_in_Average_T_G

integer

Default: 10

Labmda_AC

integer

Default: 20

Labmda_Patch_KL

number

Default: 0.065

Preform_Noise_Correction

boolean

Default: true

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

npx create-replicate --model=camenduru/renoise-inversion

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

const output = await replicate.run(
  "camenduru/renoise-inversion:c21e3ec459dd25d07650fcadb8c4e5c2601e271abc0bbac4e4ce1016010403d2",
  {
    input: {
      Labmda_AC: 20,
      Source_Prompt: "A kitten is sitting in a basket on a branch",
      Target_Prompt: "a lego kitten is sitting in a basket on a branch",
      Labmda_Patch_KL: 0.065,
      Inversion_Strength: 1,
      Preform_Noise_Correction: true,
      Number_of_ReNoise_Iterations: 9,
      Preform_Estimation_Averaging: true,
      Last_Estimation_in_Average_T_G: 10,
      Last_Estimation_in_Average_T_L: 5,
      First_Estimation_in_Average_T_G: 8,
      First_Estimation_in_Average_T_L: 0,
      Denoise_Classifier_Free_Guidence_Scale: 1
    }
  }
);

// 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=<paste-your-token-here>

Find your API token in your account settings.

Import the client:

import replicate

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

output = replicate.run(
    "camenduru/renoise-inversion:c21e3ec459dd25d07650fcadb8c4e5c2601e271abc0bbac4e4ce1016010403d2",
    input={
        "Labmda_AC": 20,
        "Source_Prompt": "A kitten is sitting in a basket on a branch",
        "Target_Prompt": "a lego kitten is sitting in a basket on a branch",
        "Labmda_Patch_KL": 0.065,
        "Inversion_Strength": 1,
        "Preform_Noise_Correction": True,
        "Number_of_ReNoise_Iterations": 9,
        "Preform_Estimation_Averaging": True,
        "Last_Estimation_in_Average_T_G": 10,
        "Last_Estimation_in_Average_T_L": 5,
        "First_Estimation_in_Average_T_G": 8,
        "First_Estimation_in_Average_T_L": 0,
        "Denoise_Classifier_Free_Guidence_Scale": 1
    }
)
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/renoise-inversion 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": "c21e3ec459dd25d07650fcadb8c4e5c2601e271abc0bbac4e4ce1016010403d2",
    "input": {
      "Labmda_AC": 20,
      "Source_Prompt": "A kitten is sitting in a basket on a branch",
      "Target_Prompt": "a lego kitten is sitting in a basket on a branch",
      "Labmda_Patch_KL": 0.065,
      "Inversion_Strength": 1,
      "Preform_Noise_Correction": true,
      "Number_of_ReNoise_Iterations": 9,
      "Preform_Estimation_Averaging": true,
      "Last_Estimation_in_Average_T_G": 10,
      "Last_Estimation_in_Average_T_L": 5,
      "First_Estimation_in_Average_T_G": 8,
      "First_Estimation_in_Average_T_L": 0,
      "Denoise_Classifier_Free_Guidence_Scale": 1
    }
  }' \
  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/renoise-inversion@sha256:c21e3ec459dd25d07650fcadb8c4e5c2601e271abc0bbac4e4ce1016010403d2 \
  -i 'Labmda_AC=20' \
  -i 'Source_Prompt="A kitten is sitting in a basket on a branch"' \
  -i 'Target_Prompt="a lego kitten is sitting in a basket on a branch"' \
  -i 'Labmda_Patch_KL=0.065' \
  -i 'Inversion_Strength=1' \
  -i 'Preform_Noise_Correction=true' \
  -i 'Number_of_ReNoise_Iterations=9' \
  -i 'Preform_Estimation_Averaging=true' \
  -i 'Last_Estimation_in_Average_T_G=10' \
  -i 'Last_Estimation_in_Average_T_L=5' \
  -i 'First_Estimation_in_Average_T_G=8' \
  -i 'First_Estimation_in_Average_T_L=0' \
  -i 'Denoise_Classifier_Free_Guidence_Scale=1'

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/renoise-inversion@sha256:c21e3ec459dd25d07650fcadb8c4e5c2601e271abc0bbac4e4ce1016010403d2
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "Labmda_AC": 20,
      "Source_Prompt": "A kitten is sitting in a basket on a branch",
      "Target_Prompt": "a lego kitten is sitting in a basket on a branch",
      "Labmda_Patch_KL": 0.065,
      "Inversion_Strength": 1,
      "Preform_Noise_Correction": true,
      "Number_of_ReNoise_Iterations": 9,
      "Preform_Estimation_Averaging": true,
      "Last_Estimation_in_Average_T_G": 10,
      "Last_Estimation_in_Average_T_L": 5,
      "First_Estimation_in_Average_T_G": 8,
      "First_Estimation_in_Average_T_L": 0,
      "Denoise_Classifier_Free_Guidence_Scale": 1
    }
  }' \
  http://localhost:5000/predictions

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

Output

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