archcollege/voice – Run with an API on Replicate

archcollege / voice

Cold

Public
49 runs
L40S

Run with an API

Playground API Examples README Versions

Input

train_audio

file

请输入要训练的声音文件.建议10-20分钟

total_epoch

integer

总训练轮数

Default: 20

if_f0_3

boolean

模型是否带音高指导(唱歌一定要, 语音可以不要)

Default: false

f0method8

string

选择音高提取算法:输入歌声可用pm提速,高质量语音但CPU差可用dio提速,harvest质量更好但慢,rmvpe效果最好且微吃CPU/GPU

Default: "harvest"

if_cache_gpu17

boolean

是否缓存所有训练集至显存. 10min以下小数据可缓存以加速训练, 大数据缓存会炸显存也加不了多少速

Default: false

audio_pth

file

(推理音频用)请输入训练好的声音模型

audio

file

(推理音频用)请输入需要合成的声音源文件

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

npx create-replicate --model=archcollege/voice

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

const output = await replicate.run(
  "archcollege/voice:218ae059b2ede4e9851ce745e6f5481a397d3374016a0a9eda5a55a10e5f64d6",
  {
    input: {
      if_f0_3: false,
      f0method8: "harvest",
      total_epoch: 20,
      if_cache_gpu17: false
    }
  }
);
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 archcollege/voice using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "archcollege/voice:218ae059b2ede4e9851ce745e6f5481a397d3374016a0a9eda5a55a10e5f64d6",
    input={
        "if_f0_3": False,
        "f0method8": "harvest",
        "total_epoch": 20,
        "if_cache_gpu17": False
    }
)
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 archcollege/voice 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": "218ae059b2ede4e9851ce745e6f5481a397d3374016a0a9eda5a55a10e5f64d6",
    "input": {
      "if_f0_3": false,
      "f0method8": "harvest",
      "total_epoch": 20,
      "if_cache_gpu17": false
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

No output yet! Press "Submit" to start a prediction.

Run time and cost

This model runs on Nvidia L40S GPU hardware. We don't yet have enough runs of this model to provide performance information.

Readme

This model doesn't have a readme.