jigsawstack / tts

text: hi there, how are you ?
accent: en-US-female-27
api_key: sk_ba8d51db7829aef7ec445bb80dd59b7ff2c320d851eb6ae4cf41aacfab4df81c690774957983ebcc02f08429fccdfe42b4d8ee6a40b404399c10ca3bcabdbb72024KnIELzWIzzblw1gtM6
return_type: binary

{
  "text": "hi there, how are you ?",
  "accent": "en-US-female-27",
  "api_key": "sk_ba8d51db7829aef7ec445bb80dd59b7ff2c320d851eb6ae4cf41aacfab4df81c690774957983ebcc02f08429fccdfe42b4d8ee6a40b404399c10ca3bcabdbb72024KnIELzWIzzblw1gtM6",
  "return_type": "binary"
}

Install Replicate’s Node.js client library:

npm install replicate

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

const output = await replicate.run(
  "jigsawstack/tts:d606ddfc5e1541356c2095b71d7d8d69c8188867e33ba2f69b9b53d6702c8f36",
  {
    input: {
      text: "hi there, how are you ?",
      accent: "en-US-female-27",
      api_key: "sk_ba8d51db7829aef7ec445bb80dd59b7ff2c320d851eb6ae4cf41aacfab4df81c690774957983ebcc02f08429fccdfe42b4d8ee6a40b404399c10ca3bcabdbb72024KnIELzWIzzblw1gtM6",
      return_type: "binary"
    }
  }
);

// 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

Import the client:

import replicate

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

output = replicate.run(
    "jigsawstack/tts:d606ddfc5e1541356c2095b71d7d8d69c8188867e33ba2f69b9b53d6702c8f36",
    input={
        "text": "hi there, how are you ?",
        "accent": "en-US-female-27",
        "api_key": "sk_ba8d51db7829aef7ec445bb80dd59b7ff2c320d851eb6ae4cf41aacfab4df81c690774957983ebcc02f08429fccdfe42b4d8ee6a40b404399c10ca3bcabdbb72024KnIELzWIzzblw1gtM6",
        "return_type": "binary"
    }
)

# 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.

Run jigsawstack/tts 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": "jigsawstack/tts:d606ddfc5e1541356c2095b71d7d8d69c8188867e33ba2f69b9b53d6702c8f36",
    "input": {
      "text": "hi there, how are you ?",
      "accent": "en-US-female-27",
      "api_key": "sk_ba8d51db7829aef7ec445bb80dd59b7ff2c320d851eb6ae4cf41aacfab4df81c690774957983ebcc02f08429fccdfe42b4d8ee6a40b404399c10ca3bcabdbb72024KnIELzWIzzblw1gtM6",
      "return_type": "binary"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

You can run this model locally using Cog. First, install Cog:

brew install cog

If you don’t have Homebrew, there are other installation options available.

Run this to download the model and run it in your local environment:

cog predict r8.im/jigsawstack/tts@sha256:d606ddfc5e1541356c2095b71d7d8d69c8188867e33ba2f69b9b53d6702c8f36 \
  -i 'text="hi there, how are you ?"' \
  -i 'accent="en-US-female-27"' \
  -i 'api_key="sk_ba8d51db7829aef7ec445bb80dd59b7ff2c320d851eb6ae4cf41aacfab4df81c690774957983ebcc02f08429fccdfe42b4d8ee6a40b404399c10ca3bcabdbb72024KnIELzWIzzblw1gtM6"' \
  -i 'return_type="binary"'

To learn more, take a look at the Cog documentation.

Run this to download the model and run it in your local environment:

docker run -d -p 5000:5000 r8.im/jigsawstack/tts@sha256:d606ddfc5e1541356c2095b71d7d8d69c8188867e33ba2f69b9b53d6702c8f36
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "text": "hi there, how are you ?",
      "accent": "en-US-female-27",
      "api_key": "sk_ba8d51db7829aef7ec445bb80dd59b7ff2c320d851eb6ae4cf41aacfab4df81c690774957983ebcc02f08429fccdfe42b4d8ee6a40b404399c10ca3bcabdbb72024KnIELzWIzzblw1gtM6",
      "return_type": "binary"
    }
  }' \
  http://localhost:5000/predictions

To learn more, take a look at the Cog documentation.