Prediction

Model

alphanumericuser/kokoro-82m:89b6fa84

ID

619hq7zekxrga0cmwytbygnj4r

Status

Succeeded

Source

Web

Hardware

T4

Total duration

2m

Created

10 months ago

Webhook

–

Input

text: Kokoro is an open-weight TTS model with 82 million parameters. Despite its lightweight architecture, it delivers comparable quality to larger models while being significantly faster and more cost-efficient. With Apache-licensed weights, Kokoro can be deployed anywhere from production environments to personal projects.
language_code: a
voice: af_heart
speed: 1

{
  "language_code": "a",
  "speed": 1,
  "text": "Kokoro is an open-weight TTS model with 82 million parameters. Despite its lightweight architecture, it delivers comparable quality to larger models while being significantly faster and more cost-efficient. With Apache-licensed weights, Kokoro can be deployed anywhere from production environments to personal projects.",
  "voice": "af_heart"
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_Ehc**********************************

This is your API token. Keep it to yourself.

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 alphanumericuser/kokoro-82m using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "alphanumericuser/kokoro-82m:89b6fa84e4fa2dd6bd3a96be3e1f12827a3516c9fda8fddbac7a0be131c9a6f5",
  {
    input: {
      language_code: "a",
      speed: 1,
      text: "Kokoro is an open-weight TTS model with 82 million parameters. Despite its lightweight architecture, it delivers comparable quality to larger models while being significantly faster and more cost-efficient. With Apache-licensed weights, Kokoro can be deployed anywhere from production environments to personal projects.",
      voice: "af_heart"
    }
  }
);

// 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=r8_Ehc**********************************

This is your API token. Keep it to yourself.

Import the client:

import replicate

Run alphanumericuser/kokoro-82m using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "alphanumericuser/kokoro-82m:89b6fa84e4fa2dd6bd3a96be3e1f12827a3516c9fda8fddbac7a0be131c9a6f5",
    input={
        "language_code": "a",
        "speed": 1,
        "text": "Kokoro is an open-weight TTS model with 82 million parameters. Despite its lightweight architecture, it delivers comparable quality to larger models while being significantly faster and more cost-efficient. With Apache-licensed weights, Kokoro can be deployed anywhere from production environments to personal projects.",
        "voice": "af_heart"
    }
)

# To access the file URL:
print(output.url())
#=> "http://example.com"

# To write the file to disk:
with open("my-image.png", "wb") as file:
    file.write(output.read())

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=r8_Ehc**********************************

This is your API token. Keep it to yourself.

Run alphanumericuser/kokoro-82m 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": "alphanumericuser/kokoro-82m:89b6fa84e4fa2dd6bd3a96be3e1f12827a3516c9fda8fddbac7a0be131c9a6f5",
    "input": {
      "language_code": "a",
      "speed": 1,
      "text": "Kokoro is an open-weight TTS model with 82 million parameters. Despite its lightweight architecture, it delivers comparable quality to larger models while being significantly faster and more cost-efficient. With Apache-licensed weights, Kokoro can be deployed anywhere from production environments to personal projects.",
      "voice": "af_heart"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "id": "619hq7zekxrga0cmwytbygnj4r",
  "model": "alphanumericuser/kokoro-82m",
  "version": "89b6fa84e4fa2dd6bd3a96be3e1f12827a3516c9fda8fddbac7a0be131c9a6f5",
  "input": {
    "language_code": "a",
    "speed": 1,
    "text": "Kokoro is an open-weight TTS model with 82 million parameters. Despite its lightweight architecture, it delivers comparable quality to larger models while being significantly faster and more cost-efficient. With Apache-licensed weights, Kokoro can be deployed anywhere from production environments to personal projects.",
    "voice": "af_heart"
  },
  "logs": "/usr/local/lib/python3.10/site-packages/torch/nn/modules/rnn.py:123: UserWarning: dropout option adds dropout after all but last recurrent layer, so non-zero dropout expects num_layers greater than 1, but got dropout=0.2 and num_layers=1\nwarnings.warn(\n/usr/local/lib/python3.10/site-packages/torch/nn/utils/weight_norm.py:143: FutureWarning: `torch.nn.utils.weight_norm` is deprecated in favor of `torch.nn.utils.parametrizations.weight_norm`.\nWeightNorm.apply(module, name, dim)\nCollecting en-core-web-sm==3.8.0\nDownloading https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-3.8.0/en_core_web_sm-3.8.0-py3-none-any.whl (12.8 MB)\n     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 12.8/12.8 MB 58.5 MB/s eta 0:00:00\nInstalling collected packages: en-core-web-sm\nSuccessfully installed en-core-web-sm-3.8.0\nWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\n[notice] A new release of pip is available: 23.0.1 -> 25.0\n[notice] To update, run: pip install --upgrade pip\n\u001b[38;5;2m✔ Download and installation successful\u001b[0m\nYou can now load the package via spacy.load('en_core_web_sm')",
  "output": "https://replicate.delivery/czjl/8Mw94y2JN3o9HhK30eokfeqq2EotPllY2D9USqXDIe34tj1QB/tmpyulkh5io.wav",
  "data_removed": false,
  "error": null,
  "source": "web",
  "status": "succeeded",
  "created_at": "2025-02-08T22:36:22.047Z",
  "started_at": "2025-02-08T22:38:04.284467Z",
  "completed_at": "2025-02-08T22:38:22.285663Z",
  "urls": {
    "cancel": "https://api.replicate.com/v1/predictions/619hq7zekxrga0cmwytbygnj4r/cancel",
    "get": "https://api.replicate.com/v1/predictions/619hq7zekxrga0cmwytbygnj4r",
    "stream": "https://stream.replicate.com/v1/files/fddq-232yowacugrpqt7qdinzo6q2gbkp4ucyzztpikgcxrvey3zubw4q",
    "web": "https://replicate.com/p/619hq7zekxrga0cmwytbygnj4r"
  },
  "metrics": {
    "predict_time": 18.001196151,
    "total_time": 120.238663
  }
}

Generated in

18.0 seconds

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