camenduru/renoise-inversion:bcd108aa – Run with an API on Replicate

Version

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camenduru /renoise-inversion:bcd108aa

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: 1

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:bcd108aa40903c0fd1a6f1788c3d9364658a700499d44622d86d561e6581a25a",
  {
    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: 1,
      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:bcd108aa40903c0fd1a6f1788c3d9364658a700499d44622d86d561e6581a25a",
    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": 1,
        "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": "bcd108aa40903c0fd1a6f1788c3d9364658a700499d44622d86d561e6581a25a",
    "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": 1,
      "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.

Output

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