fofr/musicgen-tron – Run with an API on Replicate

fofr / musicgen-tron

MusicGen fine-tuned on Tron

Cold

Public
179 runs
L40S

Run with an API

Playground API Examples README Versions

Input

prompt

string

Shift + Return to add a new line

A description of the music you want to generate.

input_audio

file

An audio file that will influence the generated music. If `continuation` is `True`, the generated music will be a continuation of the audio file. Otherwise, the generated music will mimic the audio file's melody.

duration

integer

Duration of the generated audio in seconds.

Default: 8

continuation

boolean

If `True`, generated music will continue `melody`. Otherwise, generated music will mimic `audio_input`'s melody.

Default: false

continuation_start

integer

(minimum: 0)

Start time of the audio file to use for continuation.

Default: 0

continuation_end

integer

(minimum: 0)

End time of the audio file to use for continuation. If -1 or None, will default to the end of the audio clip.

multi_band_diffusion

boolean

If `True`, the EnCodec tokens will be decoded with MultiBand Diffusion. Only works with non-stereo models.

Default: false

normalization_strategy

string

Strategy for normalizing audio.

Default: "loudness"

top_k

integer

Reduces sampling to the k most likely tokens.

Default: 250

top_p

number

Reduces sampling to tokens with cumulative probability of p. When set to `0` (default), top_k sampling is used.

Default: 0

temperature

number

Controls the 'conservativeness' of the sampling process. Higher temperature means more diversity.

Default: 1

classifier_free_guidance

integer

Increases the influence of inputs on the output. Higher values produce lower-varience outputs that adhere more closely to inputs.

Default: 3

output_format

string

Output format for generated audio.

Default: "wav"

seed

integer

Seed for random number generator. If None or -1, a random seed will be used.

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

npx create-replicate --model=fofr/musicgen-tron

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 fofr/musicgen-tron using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "fofr/musicgen-tron:d7fe672bfac1a8f1d659c790688a6e1814e4538a7885a765c78d2f382107315b",
  {
    input: {
      top_k: 250,
      top_p: 0,
      prompt: "tron, daft punk, cyberpunk",
      duration: 8,
      temperature: 1,
      continuation: false,
      output_format: "wav",
      continuation_start: 0,
      multi_band_diffusion: false,
      normalization_strategy: "loudness",
      classifier_free_guidance: 3
    }
  }
);
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 fofr/musicgen-tron using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "fofr/musicgen-tron:d7fe672bfac1a8f1d659c790688a6e1814e4538a7885a765c78d2f382107315b",
    input={
        "top_k": 250,
        "top_p": 0,
        "prompt": "tron, daft punk, cyberpunk",
        "duration": 8,
        "temperature": 1,
        "continuation": False,
        "output_format": "wav",
        "continuation_start": 0,
        "multi_band_diffusion": False,
        "normalization_strategy": "loudness",
        "classifier_free_guidance": 3
    }
)
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 fofr/musicgen-tron 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": "d7fe672bfac1a8f1d659c790688a6e1814e4538a7885a765c78d2f382107315b",
    "input": {
      "top_k": 250,
      "top_p": 0,
      "prompt": "tron, daft punk, cyberpunk",
      "duration": 8,
      "temperature": 1,
      "continuation": false,
      "output_format": "wav",
      "continuation_start": 0,
      "multi_band_diffusion": false,
      "normalization_strategy": "loudness",
      "classifier_free_guidance": 3
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Video Player is loading.

Current Time 00:00:000

Duration 00:00:000

Loaded: 0%

Stream Type LIVE

Remaining Time 00:00:000

{
  "completed_at": "2023-10-18T11:44:19.157194Z",
  "created_at": "2023-10-18T11:40:26.962746Z",
  "data_removed": false,
  "error": null,
  "id": "nqpmg3db7z4f2pxa7jt2dgxhfi",
  "input": {
    "top_k": 250,
    "top_p": 0,
    "prompt": "tron, daft punk, cyberpunk",
    "duration": 8,
    "temperature": 1,
    "continuation": false,
    "output_format": "wav",
    "continuation_start": 0,
    "multi_band_diffusion": false,
    "normalization_strategy": "loudness",
    "classifier_free_guidance": 3
  },
  "logs": "Downloading: \"https://pbxt.replicate.delivery/4DOiM3IPbRJGKtTaD6Bg7T0x09fGNST7ptARVuFN5h5NXr3IA/trained_model.tar\" to /src/models/hub/checkpoints/trained_model.tar\n  0%|          | 0.00/6.85G [00:00<?, ?B/s]\n  0%|          | 6.75M/6.85G [00:00<01:50, 66.5MB/s]\n  0%|          | 13.1M/6.85G [00:00<02:08, 57.0MB/s]\n  0%|          | 18.6M/6.85G [00:00<02:20, 52.1MB/s]\n  0%|          | 25.3M/6.85G [00:00<02:10, 56.3MB/s]\n  0%|          | 32.0M/6.85G [00:00<02:00, 60.7MB/s]\n  1%|          | 37.9M/6.85G [00:00<02:06, 58.0MB/s]\n  1%|          | 43.5M/6.85G [00:00<02:13, 54.8MB/s]\n  1%|          | 48.8M/6.85G [00:00<02:25, 50.2MB/s]\n  1%|          | 55.8M/6.85G [00:01<02:37, 46.2MB/s]\n  1%|          | 62.0M/6.85G [00:01<02:23, 50.8MB/s]\n  1%|          | 67.3M/6.85G [00:01<02:20, 51.7MB/s]\n  1%|          | 72.4M/6.85G [00:01<02:28, 48.9MB/s]\n  1%|          | 79.5M/6.85G [00:01<02:11, 55.3MB/s]\n  1%|          | 85.0M/6.85G [00:01<02:22, 51.1MB/s]\n  1%|▏         | 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[00:00<?, ?B/s]\nDownloading (…)lve/main/config.json: 100%|██████████| 758/758 [00:00<00:00, 876kB/s]\nDownloading model.safetensors:   0%|          | 0.00/236M [00:00<?, ?B/s]\nDownloading model.safetensors:  27%|██▋       | 62.9M/236M [00:00<00:00, 563MB/s]\nDownloading model.safetensors:  53%|█████▎    | 126M/236M [00:00<00:00, 582MB/s] \nDownloading model.safetensors:  80%|███████▉  | 189M/236M [00:00<00:00, 532MB/s]\nDownloading model.safetensors: 100%|██████████| 236M/236M [00:00<00:00, 546MB/s]\nUsing seed 1146090136\n1 /    400\n2 /    400\n3 /    400\n4 /    400\n5 /    400\n6 /    400\n7 /    400\n8 /    400\n9 /    400\n10 /    400\n11 /    400\n12 /    400\n13 /    400\n14 /    400\n15 /    400\n16 /    400\n17 /    400\n18 /    400\n19 /    400\n20 /    400\n21 /    400\n22 /    400\n23 /    400\n24 /    400\n25 /    400\n26 /    400\n27 /    400\n28 /    400\n29 /    400\n30 /    400\n31 /    400\n32 /    400\n33 /    400\n34 /    400\n35 /    400\n36 /    400\n37 /    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400\n398 /    400\n399 /    400\n400 /    400\n401 /    400\n402 /    400\n403 /    400\nCLIPPING out happening with proba (a bit of clipping is okay): 7.42187476134859e-05 maximum scale:  1.162497639656067",
  "metrics": {
    "predict_time": 151.636558,
    "total_time": 232.194448
  },
  "output": "https://pbxt.replicate.delivery/baUUM6VX3mqDLlAMFL2igTkLQ6rWWXE6SfCIA55LafnScXvRA/out.wav",
  "started_at": "2023-10-18T11:41:47.520636Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/nqpmg3db7z4f2pxa7jt2dgxhfi",
    "cancel": "https://api.replicate.com/v1/predictions/nqpmg3db7z4f2pxa7jt2dgxhfi/cancel"
  },
  "version": "d7fe672bfac1a8f1d659c790688a6e1814e4538a7885a765c78d2f382107315b"
}

Generated in

2 minutes 32 seconds

Tweak itReport

Downloading: "https://pbxt.replicate.delivery/4DOiM3IPbRJGKtTaD6Bg7T0x09fGNST7ptARVuFN5h5NXr3IA/trained_model.tar" to /src/models/hub/checkpoints/trained_model.tar
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CLIPPING out happening with proba (a bit of clipping is okay): 7.42187476134859e-05 maximum scale:  1.162497639656067

Run time and cost

This model costs approximately $0.17 to run on Replicate, or 5 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 L40S GPU hardware. Predictions typically complete within 3 minutes. The predict time for this model varies significantly based on the inputs.

Readme

This model doesn't have a readme.