mtg/music-approachability-engagement:386cb3ec | Run with an API on Replicate

Version

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mtg /music-approachability-engagement:386cb3ec

Playground API

Input

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audio

file

Audio file to process

url

string

Shift + Return to add a new line

https://www.youtube.com/watch?v=7zp1TbLFPp8https://www.youtube.com/watch?v=7zp1TbLFPp8

YouTube URL to process (overrides audio input)

model_type

string

Regards to the downstream type: 2class, 3class, regression

Default: "effnet-discogs-test-3class"

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

npx create-replicate --model=mtg/music-approachability-engagement

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";
import fs from "node:fs";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run mtg/music-approachability-engagement using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "mtg/music-approachability-engagement:386cb3ecc816d9486eb1d643a5ae02f74707c82dc1178613644ced06371b8f96",
  {
    input: {
      url: "https://www.youtube.com/watch?v=7zp1TbLFPp8",
      audio: "https://replicate.delivery/mgxm/3a90482a-2a14-435d-8c26-7cb5cb44b5d8/edm.mp3",
      model_type: "effnet-discogs-test-3class"
    }
  }
);

// 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 mtg/music-approachability-engagement using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "mtg/music-approachability-engagement:386cb3ecc816d9486eb1d643a5ae02f74707c82dc1178613644ced06371b8f96",
    input={
        "url": "https://www.youtube.com/watch?v=7zp1TbLFPp8",
        "audio": "https://replicate.delivery/mgxm/3a90482a-2a14-435d-8c26-7cb5cb44b5d8/edm.mp3",
        "model_type": "effnet-discogs-test-3class"
    }
)
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 mtg/music-approachability-engagement 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": "mtg/music-approachability-engagement:386cb3ecc816d9486eb1d643a5ae02f74707c82dc1178613644ced06371b8f96",
    "input": {
      "url": "https://www.youtube.com/watch?v=7zp1TbLFPp8",
      "audio": "https://replicate.delivery/mgxm/3a90482a-2a14-435d-8c26-7cb5cb44b5d8/edm.mp3",
      "model_type": "effnet-discogs-test-3class"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Rendering markdown...

{
  "completed_at": "2023-05-25T09:53:38.577233Z",
  "created_at": "2023-05-25T09:53:26.782312Z",
  "data_removed": false,
  "error": null,
  "id": "xuwomftygrhdppkrydkex7uxem",
  "input": {
    "url": "https://www.youtube.com/watch?v=7zp1TbLFPp8",
    "audio": "https://replicate.delivery/mgxm/3a90482a-2a14-435d-8c26-7cb5cb44b5d8/edm.mp3",
    "model_type": "effnet-discogs-test-3class"
  },
  "logs": "Warning: Both `url` and `audio` inputs were specified. The `url` will be process. To process the `audio` input clear the `url` input field.\n[youtube] 7zp1TbLFPp8: Downloading webpage\n[youtube] 7zp1TbLFPp8: Downloading player 41b8bed0\n[dashsegments] Total fragments: 1\n[download] Destination: /tmp/tmpcrpzmo5l/audio.webm\n[download]   0.0% of ~3.69MiB at 12.07KiB/s ETA 05:13\n[download]   0.1% of ~3.69MiB at 36.14KiB/s ETA 01:44\n[download]   0.2% of ~3.69MiB at 84.15KiB/s ETA 00:44\n[download]   0.4% of ~3.69MiB at 179.39KiB/s ETA 00:20\n[download]   0.8% of ~3.69MiB at 365.14KiB/s ETA 00:10\n[download]   1.7% of ~3.69MiB at 628.36KiB/s ETA 00:05\n[download]   3.4% of ~3.69MiB at  1.10MiB/s ETA 00:03\n[download]   6.7% of ~3.69MiB at  1.88MiB/s ETA 00:01\n[download]  13.5% of ~3.69MiB at  3.60MiB/s ETA 00:00\n[download]  27.0% of ~3.69MiB at  5.76MiB/s ETA 00:00\n[download]  54.1% of ~3.69MiB at  9.47MiB/s ETA 00:00\n[download] 100.0% of ~3.69MiB at 16.50MiB/s ETA 00:00\n[download] 100.0% of ~3.69MiB at 16.45MiB/s ETA 00:00\n[download] 100% of 3.69MiB in 00:00\n[ffmpeg] Destination: /tmp/tmpcrpzmo5l/audio.wav\nDeleting original file /tmp/tmpcrpzmo5l/audio.webm (pass -k to keep)\nloading audio...\nrunning classification heads...\n2023-05-25 09:53:35.885714: I tensorflow/core/platform/profile_utils/cpu_utils.cc:114] CPU Frequency: 2299995000 Hz\n[   INFO   ] TensorflowPredict: Successfully loaded graph file: `/models/approachability-3class.pb`\n[   INFO   ] TensorflowPredict: Successfully loaded graph file: `/models/engagement-3class.pb`\ndone!",
  "metrics": {
    "predict_time": 11.739723,
    "total_time": 11.794921
  },
  "output": "https://replicate.delivery/pbxt/9QHmo1buBp5TOhJVliul8HWMnaZgacRChRVyeD3IK5JREnfQA/out.md",
  "started_at": "2023-05-25T09:53:26.837510Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/xuwomftygrhdppkrydkex7uxem",
    "cancel": "https://api.replicate.com/v1/predictions/xuwomftygrhdppkrydkex7uxem/cancel"
  },
  "version": "386cb3ecc816d9486eb1d643a5ae02f74707c82dc1178613644ced06371b8f96"
}

Generated in

11.7 seconds

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