typetext
{
"alpha": 0.3,
"beta": 0.7,
"diffusion_steps": 10,
"embedding_scale": 1.5,
"seed": 0,
"text": "StyleTTS 2 is a text-to-speech model that leverages style diffusion and adversarial training with large speech language models to achieve human-level text-to-speech synthesis."
}npm install replicate
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=r8_XsF**********************************
This is your API token. Keep it to yourself.
import Replicate from "replicate";
import fs from "node:fs";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});
Run adirik/styletts2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"adirik/styletts2:53fd5081feae9440974d1ef9cae83bf7af5fe18be1646343f37e559f5f80a613",
{
input: {
alpha: 0.3,
beta: 0.7,
diffusion_steps: 10,
embedding_scale: 1.5,
seed: 0,
text: "StyleTTS 2 is a text-to-speech model that leverages style diffusion and adversarial training with large speech language models to achieve human-level text-to-speech synthesis."
}
}
);
// 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.
pip install replicate
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=r8_XsF**********************************
This is your API token. Keep it to yourself.
import replicate
Run adirik/styletts2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"adirik/styletts2:53fd5081feae9440974d1ef9cae83bf7af5fe18be1646343f37e559f5f80a613",
input={
"alpha": 0.3,
"beta": 0.7,
"diffusion_steps": 10,
"embedding_scale": 1.5,
"seed": 0,
"text": "StyleTTS 2 is a text-to-speech model that leverages style diffusion and adversarial training with large speech language models to achieve human-level text-to-speech synthesis."
}
)
# 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.
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=r8_XsF**********************************
This is your API token. Keep it to yourself.
Run adirik/styletts2 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": "adirik/styletts2:53fd5081feae9440974d1ef9cae83bf7af5fe18be1646343f37e559f5f80a613",
"input": {
"alpha": 0.3,
"beta": 0.7,
"diffusion_steps": 10,
"embedding_scale": 1.5,
"seed": 0,
"text": "StyleTTS 2 is a text-to-speech model that leverages style diffusion and adversarial training with large speech language models to achieve human-level text-to-speech synthesis."
}
}' \
https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
{
"id": "ehv426rccpf2wzjpe4yon6oahq",
"model": "adirik/styletts2",
"version": "53fd5081feae9440974d1ef9cae83bf7af5fe18be1646343f37e559f5f80a613",
"input": {
"alpha": 0.3,
"beta": 0.7,
"diffusion_steps": 10,
"embedding_scale": 1.5,
"seed": 0,
"text": "StyleTTS 2 is a text-to-speech model that leverages style diffusion and adversarial training with large speech language models to achieve human-level text-to-speech synthesis."
},
"logs": "",
"output": "https://replicate.delivery/pbxt/CehZad4ot3zvXSeotg8BVPf0rKSMdNusZ5eD6HepJwOQjzSPC/out.mp3",
"data_removed": false,
"error": null,
"source": "web",
"status": "succeeded",
"created_at": "2023-11-20T19:35:47.182253Z",
"started_at": "2023-11-20T19:35:48.978987Z",
"completed_at": "2023-11-20T19:35:54.404786Z",
"urls": {
"cancel": "https://api.replicate.com/v1/predictions/ehv426rccpf2wzjpe4yon6oahq/cancel",
"get": "https://api.replicate.com/v1/predictions/ehv426rccpf2wzjpe4yon6oahq"
},
"metrics": {
"predict_time": 5.425799,
"total_time": 7.222533
}
}