e7mac/beatnet – Run with an API on Replicate

e7mac / beatnet

Cold

Public
799 runs
T4

Run with an API

Playground API Examples README Versions

Input

Video Player is loading.

Current Time 00:00:000

Duration 00:00:000

Loaded: 0%

Stream Type LIVE

Remaining Time 00:00:000

audio

*file

Path to the input music. Supports mp3 and wav format.

click_track

boolean

Option to generate a click track.

Default: false

combine_click_track

boolean

Option to generate a click track overlaid on the audio.

Default: false

detect_downbeat

boolean

Click track should emphasize downbeats.

Default: false

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

npx create-replicate --model=e7mac/beatnet

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 e7mac/beatnet using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "e7mac/beatnet:d4e1c2fc15c5ba3e4fb0968e81c4c95ad59c6ec461b21cabbac33f9b5e617b2c",
  {
    input: {
      audio: "https://replicate.delivery/pbxt/JNFJg9bnf1DyV6TkjH645OoAd7VhevU9hdSj391R4j1rhbYb/in.mp3",
      click_track: true,
      detect_downbeat: false,
      combine_click_track: true
    }
  }
);

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 e7mac/beatnet using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "e7mac/beatnet:d4e1c2fc15c5ba3e4fb0968e81c4c95ad59c6ec461b21cabbac33f9b5e617b2c",
    input={
        "audio": "https://replicate.delivery/pbxt/JNFJg9bnf1DyV6TkjH645OoAd7VhevU9hdSj391R4j1rhbYb/in.mp3",
        "click_track": True,
        "detect_downbeat": False,
        "combine_click_track": True
    }
)
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 e7mac/beatnet 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": "e7mac/beatnet:d4e1c2fc15c5ba3e4fb0968e81c4c95ad59c6ec461b21cabbac33f9b5e617b2c",
    "input": {
      "audio": "https://replicate.delivery/pbxt/JNFJg9bnf1DyV6TkjH645OoAd7VhevU9hdSj391R4j1rhbYb/in.mp3",
      "click_track": true,
      "detect_downbeat": false,
      "combine_click_track": true
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

beats

tmp1gdxkhxxin-beats.json

click

Video Player is loading.

Current Time 00:00:000

Duration 00:00:000

Loaded: 0%

Stream Type LIVE

Remaining Time 00:00:000

combined

Video Player is loading.

Current Time 00:00:000

Duration 00:00:000

Loaded: 0%

Stream Type LIVE

Remaining Time 00:00:000

Generated in

13.6 seconds

Tweak it Report

This output was created using a different version of the model, e7mac/beatnet:d579bc73.

Run time and cost

This model costs approximately $0.0012 to run on Replicate, or 833 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 Nvidia T4 GPU hardware. Predictions typically complete within 6 seconds. The predict time for this model varies significantly based on the inputs.

Readme

This model doesn't have a readme.