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Average Ratings 0 Ratings
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.
Description
Recent advancements in text-based 3D object generation have yielded encouraging outcomes; however, leading methods generally need several GPU hours to create a single sample, which is a stark contrast to the latest generative image models capable of producing samples within seconds or minutes. In this study, we present a different approach to generating 3D objects that enables the creation of models in just 1-2 minutes using a single GPU. Our technique initiates by generating a synthetic view through a text-to-image diffusion model, followed by the development of a 3D point cloud using a second diffusion model that relies on the generated image for conditioning. Although our approach does not yet match the top-tier quality of existing methods, it offers a significantly faster sampling process, making it a valuable alternative for specific applications. Furthermore, we provide access to our pre-trained point cloud diffusion models, along with the evaluation code and additional models, available at this https URL. This contribution aims to facilitate further exploration and development in the realm of efficient 3D object generation.
API Access
Has API
No
API Access
Has API
No
Integrations
AI-FLOW
No
Amaro
No
Google Colab
No
VESSL AI
No
Pricing Details
Free
Free Trial
No
Free Version
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
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
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
MusicGen
Website
huggingface.co/spaces/facebook/MusicGen
Vendor Details
Company Name
OpenAI
Founded
2015
Country
United States
Website
openai.com/research/point-e