Prediction

Model

ttsds/bark_small:e0e4df86

5gq40x1wznrm80cmmxrt9ahprw

Status

Succeeded

Source

Web

Hardware

L40S

Total duration

2m 9s

Created

11 months ago

Webhook

–

Input

language: en
text: With tenure, Suzie'd have all the more leisure for yachting, but her publications are no good.
speaker_reference: https://replicate.delivery/pbxt/MNFXdPaUPOwYCZjZM4azsymbzE2TCV2WJXfGpeV2DrFWaSq8/example_en.wav

{
  "language": "en",
  "speaker_reference": "https://replicate.delivery/pbxt/MNFXdPaUPOwYCZjZM4azsymbzE2TCV2WJXfGpeV2DrFWaSq8/example_en.wav",
  "text": "With tenure, Suzie'd have all the more leisure for yachting, but her publications are no good."
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_cQc**********************************

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

const output = await replicate.run(
  "ttsds/bark_small:e0e4df86d3dd484bcb7b693077929005d4222d1bbdccf7afed3eccee06b0bbea",
  {
    input: {
      language: "en",
      speaker_reference: "https://replicate.delivery/pbxt/MNFXdPaUPOwYCZjZM4azsymbzE2TCV2WJXfGpeV2DrFWaSq8/example_en.wav",
      text: "With tenure, Suzie'd have all the more leisure for yachting, but her publications are no good."
    }
  }
);

// 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_cQc**********************************

This is your API token. Keep it to yourself.

Import the client:

import replicate

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

output = replicate.run(
    "ttsds/bark_small:e0e4df86d3dd484bcb7b693077929005d4222d1bbdccf7afed3eccee06b0bbea",
    input={
        "language": "en",
        "speaker_reference": "https://replicate.delivery/pbxt/MNFXdPaUPOwYCZjZM4azsymbzE2TCV2WJXfGpeV2DrFWaSq8/example_en.wav",
        "text": "With tenure, Suzie'd have all the more leisure for yachting, but her publications are no good."
    }
)

# 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_cQc**********************************

This is your API token. Keep it to yourself.

Run ttsds/bark_small 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": "ttsds/bark_small:e0e4df86d3dd484bcb7b693077929005d4222d1bbdccf7afed3eccee06b0bbea",
    "input": {
      "language": "en",
      "speaker_reference": "https://replicate.delivery/pbxt/MNFXdPaUPOwYCZjZM4azsymbzE2TCV2WJXfGpeV2DrFWaSq8/example_en.wav",
      "text": "With tenure, Suzie\'d have all the more leisure for yachting, but her publications are no good."
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "id": "5gq40x1wznrm80cmmxrt9ahprw",
  "model": "ttsds/bark_small",
  "version": "e0e4df86d3dd484bcb7b693077929005d4222d1bbdccf7afed3eccee06b0bbea",
  "input": {
    "language": "en",
    "speaker_reference": "https://replicate.delivery/pbxt/MNFXdPaUPOwYCZjZM4azsymbzE2TCV2WJXfGpeV2DrFWaSq8/example_en.wav",
    "text": "With tenure, Suzie'd have all the more leisure for yachting, but her publications are no good."
  },
  "logs": "Extracting semantics...\nTokenizing semantics...\nCreating coarse and fine prompts...\n  0%|          | 0/768 [00:00<?, ?it/s]\n  0%|          | 1/768 [00:00<02:24,  5.30it/s]\n  7%|▋         | 51/768 [00:00<00:03, 216.88it/s]\n 13%|█▎        | 101/768 [00:00<00:02, 323.91it/s]\n 20%|█▉        | 152/768 [00:00<00:01, 387.07it/s]\n 26%|██▋       | 202/768 [00:00<00:01, 422.59it/s]\n 33%|███▎      | 252/768 [00:00<00:01, 445.04it/s]\n 39%|███▉      | 303/768 [00:00<00:01, 462.92it/s]\n 46%|████▌     | 354/768 [00:00<00:00, 474.85it/s]\n 53%|█████▎    | 404/768 [00:00<00:00, 482.02it/s]\n 59%|█████▉    | 455/768 [00:01<00:00, 487.87it/s]\n 66%|██████▌   | 506/768 [00:01<00:00, 493.62it/s]\n 73%|███████▎  | 557/768 [00:01<00:00, 496.55it/s]\n100%|██████████| 594/594 [00:01<00:00, 496.55it/s]\n100%|██████████| 594/594 [00:01<00:00, 431.53it/s]\n  0%|          | 0/30 [00:00<?, ?it/s]\n  3%|▎         | 1/30 [00:00<00:03,  7.93it/s]\n  7%|▋         | 2/30 [00:00<00:03,  8.30it/s]\n 10%|█         | 3/30 [00:00<00:03,  8.45it/s]\n 13%|█▎        | 4/30 [00:00<00:03,  8.54it/s]\n 17%|█▋        | 5/30 [00:00<00:02,  8.59it/s]\n 20%|██        | 6/30 [00:00<00:02,  8.59it/s]\n 23%|██▎       | 7/30 [00:00<00:02,  8.64it/s]\n 27%|██▋       | 8/30 [00:00<00:02,  8.67it/s]\n 30%|███       | 9/30 [00:01<00:02,  8.70it/s]\n 33%|███▎      | 10/30 [00:01<00:02,  8.72it/s]\n 37%|███▋      | 11/30 [00:01<00:02,  8.73it/s]\n 40%|████      | 12/30 [00:01<00:02,  8.73it/s]\n 43%|████▎     | 13/30 [00:01<00:01,  8.74it/s]\n 47%|████▋     | 14/30 [00:01<00:01,  8.73it/s]\n 50%|█████     | 15/30 [00:01<00:01,  8.73it/s]\n 53%|█████▎    | 16/30 [00:01<00:01,  8.74it/s]\n 57%|█████▋    | 17/30 [00:01<00:01,  8.75it/s]\n 60%|██████    | 18/30 [00:02<00:01,  8.75it/s]\n 63%|██████▎   | 19/30 [00:02<00:01,  8.75it/s]\n 67%|██████▋   | 20/30 [00:02<00:01,  8.69it/s]\n 70%|███████   | 21/30 [00:02<00:01,  8.70it/s]\n 73%|███████▎  | 22/30 [00:02<00:00,  8.72it/s]\n 77%|███████▋  | 23/30 [00:02<00:00,  8.73it/s]\n 80%|████████  | 24/30 [00:02<00:00,  8.74it/s]\n 83%|████████▎ | 25/30 [00:02<00:00,  8.70it/s]\n 87%|████████▋ | 26/30 [00:02<00:00,  8.72it/s]\n 90%|█████████ | 27/30 [00:03<00:00,  8.71it/s]\n 93%|█████████▎| 28/30 [00:03<00:00,  8.67it/s]\n 97%|█████████▋| 29/30 [00:03<00:00,  8.69it/s]\n100%|██████████| 30/30 [00:03<00:00,  8.76it/s]",
  "output": "https://replicate.delivery/xezq/WOBvQ5Q2JlLvJhj1Erj7RUvpq585eQnFCbe31ZYgvMLEtRJUA/test_pred.wav",
  "data_removed": false,
  "error": null,
  "source": "web",
  "status": "succeeded",
  "created_at": "2025-01-27T11:06:43.837Z",
  "started_at": "2025-01-27T11:08:46.993821Z",
  "completed_at": "2025-01-27T11:08:52.457579Z",
  "urls": {
    "cancel": "https://api.replicate.com/v1/predictions/5gq40x1wznrm80cmmxrt9ahprw/cancel",
    "get": "https://api.replicate.com/v1/predictions/5gq40x1wznrm80cmmxrt9ahprw",
    "stream": "https://stream.replicate.com/v1/files/bsvm-3iproag4scqrqdwypbylyhpjd7z6shcm6f6p32sktzqokxd2cufq",
    "web": "https://replicate.com/p/5gq40x1wznrm80cmmxrt9ahprw"
  },
  "metrics": {
    "predict_time": 5.463757617,
    "total_time": 128.620579
  }
}

Generated in

5.5 seconds

Tweak it Report

Extracting semantics... Tokenizing semantics... Creating coarse and fine prompts... 0%| | 0/768 [00:00<?, ?it/s] 0%| | 1/768 [00:00<02:24, 5.30it/s] 7%|▋ | 51/768 [00:00<00:03, 216.88it/s] 13%|█▎ | 101/768 [00:00<00:02, 323.91it/s] 20%|█▉ | 152/768 [00:00<00:01, 387.07it/s] 26%|██▋ | 202/768 [00:00<00:01, 422.59it/s] 33%|███▎ | 252/768 [00:00<00:01, 445.04it/s] 39%|███▉ | 303/768 [00:00<00:01, 462.92it/s] 46%|████▌ | 354/768 [00:00<00:00, 474.85it/s] 53%|█████▎ | 404/768 [00:00<00:00, 482.02it/s] 59%|█████▉ | 455/768 [00:01<00:00, 487.87it/s] 66%|██████▌ | 506/768 [00:01<00:00, 493.62it/s] 73%|███████▎ | 557/768 [00:01<00:00, 496.55it/s] 100%|██████████| 594/594 [00:01<00:00, 496.55it/s] 100%|██████████| 594/594 [00:01<00:00, 431.53it/s] 0%| | 0/30 [00:00<?, ?it/s] 3%|▎ | 1/30 [00:00<00:03, 7.93it/s] 7%|▋ | 2/30 [00:00<00:03, 8.30it/s] 10%|█ | 3/30 [00:00<00:03, 8.45it/s] 13%|█▎ | 4/30 [00:00<00:03, 8.54it/s] 17%|█▋ | 5/30 [00:00<00:02, 8.59it/s] 20%|██ | 6/30 [00:00<00:02, 8.59it/s] 23%|██▎ | 7/30 [00:00<00:02, 8.64it/s] 27%|██▋ | 8/30 [00:00<00:02, 8.67it/s] 30%|███ | 9/30 [00:01<00:02, 8.70it/s] 33%|███▎ | 10/30 [00:01<00:02, 8.72it/s] 37%|███▋ | 11/30 [00:01<00:02, 8.73it/s] 40%|████ | 12/30 [00:01<00:02, 8.73it/s] 43%|████▎ | 13/30 [00:01<00:01, 8.74it/s] 47%|████▋ | 14/30 [00:01<00:01, 8.73it/s] 50%|█████ | 15/30 [00:01<00:01, 8.73it/s] 53%|█████▎ | 16/30 [00:01<00:01, 8.74it/s] 57%|█████▋ | 17/30 [00:01<00:01, 8.75it/s] 60%|██████ | 18/30 [00:02<00:01, 8.75it/s] 63%|██████▎ | 19/30 [00:02<00:01, 8.75it/s] 67%|██████▋ | 20/30 [00:02<00:01, 8.69it/s] 70%|███████ | 21/30 [00:02<00:01, 8.70it/s] 73%|███████▎ | 22/30 [00:02<00:00, 8.72it/s] 77%|███████▋ | 23/30 [00:02<00:00, 8.73it/s] 80%|████████ | 24/30 [00:02<00:00, 8.74it/s] 83%|████████▎ | 25/30 [00:02<00:00, 8.70it/s] 87%|████████▋ | 26/30 [00:02<00:00, 8.72it/s] 90%|█████████ | 27/30 [00:03<00:00, 8.71it/s] 93%|█████████▎| 28/30 [00:03<00:00, 8.67it/s] 97%|█████████▋| 29/30 [00:03<00:00, 8.69it/s] 100%|██████████| 30/30 [00:03<00:00, 8.76it/s]