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features
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support

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Description

AudioCraft serves as a comprehensive codebase tailored for all your generative audio requirements, including music, sound effects, and compression, following its training on raw audio signals. By utilizing AudioCraft, we enhance the design of generative audio models significantly compared to earlier methodologies. Both MusicGen and AudioGen rely on a unified autoregressive Language Model (LM) that functions across streams of compressed discrete music representations known as tokens. We propose a straightforward technique to exploit the intrinsic structure of the parallel token streams, demonstrating that with a single model and a refined interleaving pattern, we can effectively model audio sequences while capturing long-term dependencies, resulting in the generation of high-quality audio outputs. Our models utilize the EnCodec neural audio codec to derive discrete audio tokens from the raw waveform, with EnCodec transforming the audio signal into multiple parallel streams of discrete tokens. This innovative approach not only streamlines audio generation but also enhances the overall efficiency and quality of the output.

Description

Meta's MusicGen is an open-source deep-learning model designed to create short musical compositions based on textual descriptions. Trained on 20,000 hours of music, encompassing complete tracks and single instrument samples, this model produces 12 seconds of audio in response to user prompts. Additionally, users can submit reference audio to extract a general melody, which the model will incorporate alongside the provided description. All generated samples utilize the melody model, ensuring consistency. Furthermore, users have the option to run the model on their own GPUs or utilize Google Colab by following the guidelines available in the repository. MusicGen features a single-stage transformer architecture combined with efficient token interleaving techniques, which streamline the process by eliminating the need for multiple cascading models. This innovative approach enables MusicGen to generate high-quality audio samples that are responsive to both textual inputs and musical characteristics, allowing users to exert greater control over the final output. The combination of these features positions MusicGen as a versatile tool for music creation and exploration.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

AI-FLOW No 
Amaro No 
Google Colab No 
VESSL AI No 

Integrations

AI-FLOW Yes 
Amaro Yes 
Google Colab Yes 
VESSL AI Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Meta AI

Founded

2004

Country

United States

Website

audiocraft.metademolab.com

Vendor Details

Company Name

MusicGen

Website

huggingface.co/spaces/facebook/MusicGen

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