nateraw/autotune – Run with an API on Replicate

nateraw / autotune

pitch correction on your voice

Cold

Public
333 runs
CPU
GitHub

Run with an API

Playground API Examples README Versions

Input

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audio_file

*file

Audio input file

scale

string

Strategy for normalizing audio.

Default: "closest"

output_format

string

Output format for generated audio.

Default: "wav"

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

npx create-replicate --model=nateraw/autotune

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

const output = await replicate.run(
  "nateraw/autotune:53d58aea27ccd949e5f9d77e4b2a74ffe90e1fa534295b257cea50f011e233dd",
  {
    input: {
      scale: "Gb:min",
      audio_file: "https://replicate.delivery/pbxt/KlypmfOy3eCR7nfLP2XFRvXbujUFjjoUfQtIXjVrfdmfpbty/nate_is_singing_Gb_minor.wav",
      output_format: "wav"
    }
  }
);
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 nateraw/autotune using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "nateraw/autotune:53d58aea27ccd949e5f9d77e4b2a74ffe90e1fa534295b257cea50f011e233dd",
    input={
        "scale": "Gb:min",
        "audio_file": "https://replicate.delivery/pbxt/KlypmfOy3eCR7nfLP2XFRvXbujUFjjoUfQtIXjVrfdmfpbty/nate_is_singing_Gb_minor.wav",
        "output_format": "wav"
    }
)
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 nateraw/autotune 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": "53d58aea27ccd949e5f9d77e4b2a74ffe90e1fa534295b257cea50f011e233dd",
    "input": {
      "scale": "Gb:min",
      "audio_file": "https://replicate.delivery/pbxt/KlypmfOy3eCR7nfLP2XFRvXbujUFjjoUfQtIXjVrfdmfpbty/nate_is_singing_Gb_minor.wav",
      "output_format": "wav"
    }
  }' \
  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/nateraw/autotune@sha256:53d58aea27ccd949e5f9d77e4b2a74ffe90e1fa534295b257cea50f011e233dd \
  -i 'scale="Gb:min"' \
  -i 'audio_file="https://replicate.delivery/pbxt/KlypmfOy3eCR7nfLP2XFRvXbujUFjjoUfQtIXjVrfdmfpbty/nate_is_singing_Gb_minor.wav"' \
  -i 'output_format="wav"'

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/nateraw/autotune@sha256:53d58aea27ccd949e5f9d77e4b2a74ffe90e1fa534295b257cea50f011e233dd
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "scale": "Gb:min",
      "audio_file": "https://replicate.delivery/pbxt/KlypmfOy3eCR7nfLP2XFRvXbujUFjjoUfQtIXjVrfdmfpbty/nate_is_singing_Gb_minor.wav",
      "output_format": "wav"
    }
  }' \
  http://localhost:5000/predictions

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

Output

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Generated in

3.9 seconds

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Run time and cost

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

Readme

This model doesn't have a readme.