aiviostudio/salmonn-2025 – Run with an API on Replicate

aiviostudio / salmonn-2025

Cold

Public
32 runs
A100 (80GB)

Run with an API

Playground API Examples README Versions

Input

Video Player is loading.

Current Time 00:00:000

Duration 00:00:000

Loaded: 0%

Stream Type LIVE

Remaining Time 00:00:000

prompt

*string

Shift + Return to add a new line

Text prompt to guide the audio understanding

audio_file

*file

Audio file to process

num_beams

integer

Number of beams for beam search

Default: 4

temperature

number

Sampling temperature

Default: 1

top_p

number

Top p sampling parameter

Default: 0.9

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

npx create-replicate --model=aiviostudio/salmonn-2025

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 aiviostudio/salmonn-2025 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "aiviostudio/salmonn-2025:e6bd4dcfe3601efbcd9f5b5e81a4828eade396e9d2d6362c79070943862664b5",
  {
    input: {
      top_p: 0.9,
      prompt: "describe the music ",
      num_beams: 4,
      audio_file: "https://replicate.delivery/pbxt/MmG7bUBBIPLhXrG5aHh2oB8fmjmGfhaHpPygHN8X5L0PQWfk/sad-output.mp3",
      temperature: 1
    }
  }
);

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 aiviostudio/salmonn-2025 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "aiviostudio/salmonn-2025:e6bd4dcfe3601efbcd9f5b5e81a4828eade396e9d2d6362c79070943862664b5",
    input={
        "top_p": 0.9,
        "prompt": "describe the music ",
        "num_beams": 4,
        "audio_file": "https://replicate.delivery/pbxt/MmG7bUBBIPLhXrG5aHh2oB8fmjmGfhaHpPygHN8X5L0PQWfk/sad-output.mp3",
        "temperature": 1
    }
)
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 aiviostudio/salmonn-2025 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": "aiviostudio/salmonn-2025:e6bd4dcfe3601efbcd9f5b5e81a4828eade396e9d2d6362c79070943862664b5",
    "input": {
      "top_p": 0.9,
      "prompt": "describe the music ",
      "num_beams": 4,
      "audio_file": "https://replicate.delivery/pbxt/MmG7bUBBIPLhXrG5aHh2oB8fmjmGfhaHpPygHN8X5L0PQWfk/sad-output.mp3",
      "temperature": 1
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

This music can be described as a blend of rock, alternative, and indie genres. It features a mix of electric and acoustic guitars, with a focus on creating a mellow and introspective atmosphere. The lyrics explore themes of love, loss, and the passage of time. The vocals are performed by a male vocalist with a smooth and soulful voice. The overall sound is reminiscent of classic rock bands from the 70s and 80s, with a modern twist. This music would be perfect for a chill night in with friends, or as the soundtrack to a coming-of-age movie.

Generated in

33.0 seconds

Tweak it Share Report

Run time and cost

This model runs on Nvidia A100 (80GB) GPU hardware. We don't yet have enough runs of this model to provide performance information.

Readme

This model doesn't have a readme.