camenduru/metavoice – Run with an API on Replicate

camenduru / metavoice

MetaVoice-1B: 1.2B parameter base model trained on 100K hours of speech

Cold

Public
11.8K runs
L40S
GitHub
License

Run with an API

Playground API Examples README Versions

Input

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input_audio

*file

Input Image

text

string

Shift + Return to add a new line

This is a demo of text to speech by MetaVoice-1B, an open-source foundational audio model by MetaVoice.This is a demo of text to speech by MetaVoice-1B, an open-source foundational audio model by MetaVoice.

Default: "This is a demo of text to speech by MetaVoice-1B, an open-source foundational audio model by MetaVoice."

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

npx create-replicate --model=camenduru/metavoice

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

const output = await replicate.run(
  "camenduru/metavoice:713109ece68b60131018e86585221826650aba6d11ffd4e314f50c7598014358",
  {
    input: {
      text: "This is a demo of text to speech by MetaVoice-1B, an open-source foundational audio model by MetaVoice.",
      input_audio: "https://replicate.delivery/pbxt/KMZ6fyOMKrtwERmDWAJnd5KRy39a86dgloX7SYP5dVTnQXjv/jacob.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 camenduru/metavoice using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "camenduru/metavoice:713109ece68b60131018e86585221826650aba6d11ffd4e314f50c7598014358",
    input={
        "text": "This is a demo of text to speech by MetaVoice-1B, an open-source foundational audio model by MetaVoice.",
        "input_audio": "https://replicate.delivery/pbxt/KMZ6fyOMKrtwERmDWAJnd5KRy39a86dgloX7SYP5dVTnQXjv/jacob.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 camenduru/metavoice 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": "713109ece68b60131018e86585221826650aba6d11ffd4e314f50c7598014358",
    "input": {
      "text": "This is a demo of text to speech by MetaVoice-1B, an open-source foundational audio model by MetaVoice.",
      "input_audio": "https://replicate.delivery/pbxt/KMZ6fyOMKrtwERmDWAJnd5KRy39a86dgloX7SYP5dVTnQXjv/jacob.wav"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

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{
  "completed_at": "2024-02-07T16:03:53.745746Z",
  "created_at": "2024-02-07T15:59:03.489494Z",
  "data_removed": false,
  "error": null,
  "id": "opxrghlbjczjzdbpaz7vgkkr2y",
  "input": {
    "text": "This is a demo of text to speech by MetaVoice-1B, an open-source foundational audio model by MetaVoice.",
    "input_audio": "https://replicate.delivery/pbxt/KMZ6fyOMKrtwERmDWAJnd5KRy39a86dgloX7SYP5dVTnQXjv/jacob.wav"
  },
  "logs": "getting cached speaker ref files:   0%|          | 0/1 [00:00<?, ?it/s]\ngetting cached speaker ref files: 100%|██████████| 1/1 [00:00<00:00, 23431.87it/s]\ncalculating speaker embeddings:   0%|          | 0/1 [00:00<?, ?it/s]\ncalculating speaker embeddings: 100%|██████████| 1/1 [00:00<00:00, 77.62it/s]\nbatch:   0%|          | 0/1 [00:00<?, ?it/s]\ntokens:   0%|          | 0/1728 [00:00<?, ?it/s]\u001b[A\ntokens:   0%|          | 8/1728 [00:00<00:23, 73.31it/s]\u001b[A\ntokens:   1%|          | 18/1728 [00:00<00:20, 84.77it/s]\u001b[A\ntokens:   2%|▏         | 28/1728 [00:00<00:19, 88.60it/s]\u001b[A\ntokens:   2%|▏         | 38/1728 [00:00<00:18, 90.47it/s]\u001b[A\ntokens:   3%|▎         | 48/1728 [00:00<00:18, 91.73it/s]\u001b[A\ntokens:   3%|▎         | 58/1728 [00:00<00:17, 93.14it/s]\u001b[A\ntokens:   4%|▍         | 68/1728 [00:00<00:17, 93.85it/s]\u001b[A\ntokens:   5%|▍         | 78/1728 [00:00<00:18, 90.91it/s]\u001b[A\ntokens:   5%|▌         | 88/1728 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is a demo of text to speech by MetaVoice-1B, an open-source foundational audio model by MetaVoice.\nnon-causal batching:   0%|          | 0/1 [00:00<?, ?it/s]\nnon-causal batching: 100%|██████████| 1/1 [00:00<00:00, 178.65it/s]\nText: This is a demo of text to speech by MetaVoice-1B, an open-source foundational audio model by MetaVoice.\nSaved audio to /content/metavoice-src/samples/synth_This_is_a_demo_of_text_to_33dc6b0c-aefe-4bce-ae3f-d9fb0118e626.wav\n2024-02-07 16:03:52 | INFO     | DF | Loading model settings of DeepFilterNet3\n2024-02-07 16:03:52 | INFO     | DF | Using DeepFilterNet3 model at /root/.cache/DeepFilterNet/DeepFilterNet3\n2024-02-07 16:03:52 | INFO     | DF | Initializing model `deepfilternet3`\n2024-02-07 16:03:52 | INFO     | DF | Found checkpoint /root/.cache/DeepFilterNet/DeepFilterNet3/checkpoints/model_120.ckpt.best with epoch 120\n2024-02-07 16:03:52 | INFO     | DF | Running on device cuda:0\n2024-02-07 16:03:52 | INFO     | DF | Model loaded\n/usr/local/lib/python3.10/site-packages/torchaudio/functional/functional.py:1371: UserWarning: \"sinc_interpolation\" resampling method name is being deprecated and replaced by \"sinc_interp_hann\" in the next release. The default behavior remains unchanged.\nwarnings.warn(\ncopying enhanced file from /tmp/tmpee_vnj7o.wav to /content/metavoice-src/samples/synth_This_is_a_demo_of_text_to_33dc6b0c-aefe-4bce-ae3f-d9fb0118e626.wav.",
  "metrics": {
    "predict_time": 70.604136,
    "total_time": 290.256252
  },
  "output": "https://replicate.delivery/pbxt/X51koZ3NOtavHxCfpuEWjf5cpKWafRKHGtHJd4EtVUZRfWRJB/synth_This_is_a_demo_of_text_to_33dc6b0c-aefe-4bce-ae3f-d9fb0118e626.wav",
  "started_at": "2024-02-07T16:02:43.141610Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/opxrghlbjczjzdbpaz7vgkkr2y",
    "cancel": "https://api.replicate.com/v1/predictions/opxrghlbjczjzdbpaz7vgkkr2y/cancel"
  },
  "version": "713109ece68b60131018e86585221826650aba6d11ffd4e314f50c7598014358"
}

Generated in

70.6 seconds

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WARNING: Number of tokens at each hierarchy must be of the same length!
Truncating to min length of 535 tokens from 536 max.
[535, 536]
Text: This is a demo of text to speech by MetaVoice-1B, an open-source foundational audio model by MetaVoice.
non-causal batching:   0%|          | 0/1 [00:00<?, ?it/s]
non-causal batching: 100%|██████████| 1/1 [00:00<00:00, 178.65it/s]
Text: This is a demo of text to speech by MetaVoice-1B, an open-source foundational audio model by MetaVoice.
Saved audio to /content/metavoice-src/samples/synth_This_is_a_demo_of_text_to_33dc6b0c-aefe-4bce-ae3f-d9fb0118e626.wav
2024-02-07 16:03:52 | INFO     | DF | Loading model settings of DeepFilterNet3
2024-02-07 16:03:52 | INFO     | DF | Using DeepFilterNet3 model at /root/.cache/DeepFilterNet/DeepFilterNet3
2024-02-07 16:03:52 | INFO     | DF | Initializing model `deepfilternet3`
2024-02-07 16:03:52 | INFO     | DF | Found checkpoint /root/.cache/DeepFilterNet/DeepFilterNet3/checkpoints/model_120.ckpt.best with epoch 120
2024-02-07 16:03:52 | INFO     | DF | Running on device cuda:0
2024-02-07 16:03:52 | INFO     | DF | Model loaded
/usr/local/lib/python3.10/site-packages/torchaudio/functional/functional.py:1371: UserWarning: "sinc_interpolation" resampling method name is being deprecated and replaced by "sinc_interp_hann" in the next release. The default behavior remains unchanged.
warnings.warn(
copying enhanced file from /tmp/tmpee_vnj7o.wav to /content/metavoice-src/samples/synth_This_is_a_demo_of_text_to_33dc6b0c-aefe-4bce-ae3f-d9fb0118e626.wav.

Run time and cost

This model costs approximately $0.091 to run on Replicate, or 10 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 94 seconds. The predict time for this model varies significantly based on the inputs.