jimothyjohn/matchering – Run with an API on Replicate

jimothyjohn / matchering

Matchering 2.0 is a novel tool for audio matching and mastering.

Cold

Public
2 runs
CPU
GitHub
License

Run with an API

Playground API Examples README Versions

Input

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

npx create-replicate --model=jimothyjohn/matchering

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

const output = await replicate.run(
  "jimothyjohn/matchering:7add4a4f0e454bff7927944cf2050b39331f2b51a95444539626938c98e1303f",
  {
    input: {}
  }
);
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 jimothyjohn/matchering using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "jimothyjohn/matchering:7add4a4f0e454bff7927944cf2050b39331f2b51a95444539626938c98e1303f",
    input={}
)
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 jimothyjohn/matchering 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": "7add4a4f0e454bff7927944cf2050b39331f2b51a95444539626938c98e1303f",
    "input": {}
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

Install Cog

brew install cog

If you don’t have Homebrew, there are other installation options available.

Pull and run jimothyjohn/matchering using Cog (this will download the full model and run it in your local environment):

cog predict r8.im/jimothyjohn/matchering@sha256:7add4a4f0e454bff7927944cf2050b39331f2b51a95444539626938c98e1303f \

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

Pull and run jimothyjohn/matchering using Docker (this will download the full model and run it in your local environment):

docker run -d -p 5000:5000 r8.im/jimothyjohn/matchering@sha256:7add4a4f0e454bff7927944cf2050b39331f2b51a95444539626938c98e1303f
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {}
  }' \
  http://localhost:5000/predictions

Output

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

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

Matchering 2.0 is a novel tool for audio matching and mastering.

It follows a simple idea - you take TWO audio files and feed them into Matchering:

TARGET (the track you want to master, you want it to sound like the reference) REFERENCE (another track, like some kind of “wet” popular song, you want your target to sound like it)

Our algorithm matches both of these tracks and provides you the mastered TARGET track with the same RMS, FR, peak amplitude and stereo width as the REFERENCE track has.