haoheliu/audio-ldm – Run with an API on Replicate

haoheliu / audio-ldm

Text-to-audio generation with latent diffusion models

Cold

Public
37.6K runs
T4
GitHub
Paper
License

Run with an API

Playground API Examples README Versions

Input

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

npx create-replicate --model=haoheliu/audio-ldm

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 haoheliu/audio-ldm using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "haoheliu/audio-ldm:b61392adecdd660326fc9cfc5398182437dbe5e97b5decfb36e1a36de68b5b95",
  {
    input: {
      text: "two starships are fighting in space with laser cannons",
      duration: "5.0",
      n_candidates: 3,
      guidance_scale: 2.5
    }
  }
);

// 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=<paste-your-token-here>

Find your API token in your account settings.

Import the client:

import replicate

Run haoheliu/audio-ldm using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "haoheliu/audio-ldm:b61392adecdd660326fc9cfc5398182437dbe5e97b5decfb36e1a36de68b5b95",
    input={
        "text": "two starships are fighting in space with laser cannons",
        "duration": "5.0",
        "n_candidates": 3,
        "guidance_scale": 2.5
    }
)
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 haoheliu/audio-ldm 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": "haoheliu/audio-ldm:b61392adecdd660326fc9cfc5398182437dbe5e97b5decfb36e1a36de68b5b95",
    "input": {
      "text": "two starships are fighting in space with laser cannons",
      "duration": "5.0",
      "n_candidates": 3,
      "guidance_scale": 2.5
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Video Player is loading.

Current Time 00:00:000

Duration 00:00:000

Loaded: 0%

Stream Type LIVE

Remaining Time 00:00:000

{
  "completed_at": "2023-02-03T01:46:46.411968Z",
  "created_at": "2023-02-03T01:46:20.900393Z",
  "data_removed": false,
  "error": null,
  "id": "c24g2srwuvd23ascxoezjlqxfq",
  "input": {
    "text": "two starships are fighting in space with laser cannons",
    "duration": "5.0",
    "n_candidates": 3,
    "guidance_scale": 2.5
  },
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100%|██████████| 200/200 [00:23<00:00,  8.40it/s]",
  "metrics": {
    "predict_time": 25.437264,
    "total_time": 25.511575
  },
  "output": "https://replicate.delivery/pbxt/HtbbL1ngdwJLKhxE9ds3aeIWvm7r3I8e0D5VgjQ4ZLDGmhaQA/two%20starships%20are%20fighting%20in%20space%20with%20laser%20cannons.wav",
  "started_at": "2023-02-03T01:46:20.974704Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/c24g2srwuvd23ascxoezjlqxfq",
    "cancel": "https://api.replicate.com/v1/predictions/c24g2srwuvd23ascxoezjlqxfq/cancel"
  },
  "version": "b61392adecdd660326fc9cfc5398182437dbe5e97b5decfb36e1a36de68b5b95"
}

Generated in

25.4 seconds

Tweak itReport

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Run time and cost

This model costs approximately $0.069 to run on Replicate, or 14 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker.

This model runs on Nvidia T4 GPU hardware. Predictions typically complete within 6 minutes. The predict time for this model varies significantly based on the inputs.

Readme

Text-to-audio with latent diffusion

Model description

AudioLDM generates text-conditional sound effects, human speech, and music. It enables zero-shot text-guided audio style-transfer, inpainting, and super-resolution.

GitHub Demos and Project Page GitHub Repo for code

Tricks for Enhancing the Quality of Your Generated Audio

Try to use more adjectives to describe your sound. For example: “A man is speaking clearly and slowly in a large room” is better than “A man is speaking”. This can help ensure AudioLDM understands what you want.
Try using different random seeds, which can sometimes affect the generation quality.
It’s better to use general terms like ‘man’ or ‘woman’ instead of specific names for individuals or abstract objects that humans may not be familiar with.

Model Authors

Haohe Liu, Zehua Chen, Yi Yuan, Xinhao Mei, Xubo Liu, Danilo Mandic, Wenwu Wang, Mark D. Plumley