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Implementation:Facebookresearch Audiocraft MagnetApp

From Leeroopedia
Knowledge Sources
Domains Demo, Audio_Generation
Last Updated 2026-02-14 01:00 GMT

Overview

Concrete tool for running an interactive Gradio web demo of the MAGNeT text-to-music and text-to-sound generation model.

Description

MagnetApp is a Gradio web application that provides an interactive interface for the MAGNeT model. It supports text-conditioned generation for both music and environmental sound, with configurable parameters including model variant selection (small/medium, 10s/30s), temperature, top-k/top-p sampling, CFG coefficients, decoding steps, and span arrangement.

Usage

Run this application to demonstrate MAGNeT's text-to-music and text-to-sound generation capabilities through a web browser interface.

Code Reference

Source Location

Signature

def predict_full(model_path, text, temperature, top_k, top_p,
                 max_cfg_coef, min_cfg_coef, decoding_steps_1, decoding_steps_2,
                 decoding_steps_3, decoding_steps_4, span_score, span_arrangement):
    """Generate audio from text using MAGNeT model."""

Import

# Run as a standalone script
python demos/magnet_app.py

I/O Contract

Inputs

Name Type Required Description
text str Yes Text description for audio generation
model_path str Yes Pretrained model identifier
temperature float No Sampling temperature (default 3.0)
decoding_steps list[int] No Steps per codebook [20,10,10,10]

Outputs

Name Type Description
audio tuple(int, numpy.ndarray) Generated audio as (sample_rate, waveform)

Usage Examples

# Launch the demo
python demos/magnet_app.py --share

# Or programmatically:
from audiocraft.models import MAGNeT
model = MAGNeT.get_pretrained('facebook/magnet-small-10secs')
model.set_generation_params(temperature=3.0, top_p=0.9)
wav = model.generate(['dogs barking and a cat meowing'])

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