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Average Ratings 0 Ratings

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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

Seed Diffusion Preview is an advanced language model designed for code generation that employs discrete-state diffusion, allowing it to produce code in a non-sequential manner, resulting in significantly faster inference times without compromising on quality. This innovative approach utilizes a two-stage training process that involves mask-based corruption followed by edit-based augmentation, enabling a standard dense Transformer to achieve an optimal balance between speed and precision while avoiding shortcuts like carry-over unmasking, which helps maintain rigorous density estimation. The model impressively achieves an inference rate of 2,146 tokens per second on H20 GPUs, surpassing current diffusion benchmarks while either matching or exceeding their accuracy on established code evaluation metrics, including various editing tasks. This performance not only sets a new benchmark for the speed-quality trade-off in code generation but also showcases the effective application of discrete diffusion methods in practical coding scenarios. Its success opens up new avenues for enhancing efficiency in coding tasks across multiple platforms.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

AnyAPI No 
C++ No 
Citlyze No 
Flyne AI No 
Fuser No 
Go No 
Java No 
Magica No 
Python No 
TESS AI No 
WaveSpeedAI No 
ZOOOP No 
graphis No 

Integrations

AnyAPI Yes 
C++ Yes 
Citlyze Yes 
Flyne AI Yes 
Fuser Yes 
Go Yes 
Java Yes 
Magica Yes 
Python Yes 
TESS AI Yes 
WaveSpeedAI Yes 
ZOOOP Yes 
graphis 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

ByteDance

Founded

2012

Country

China

Website

seed.bytedance.com/en/seed_diffusion

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