|  |  | 
					
						
						|  |  | 
					
						
						|  |  | 
					
						
						|  |  | 
					
						
						|  |  | 
					
						
						|  | """ | 
					
						
						|  | AudioCraft is a general framework for training audio generative models. | 
					
						
						|  | At the moment we provide the training code for: | 
					
						
						|  |  | 
					
						
						|  | - [MusicGen](https://arxiv.org/abs/2306.05284), a state-of-the-art | 
					
						
						|  | text-to-music and melody+text autoregressive generative model. | 
					
						
						|  | For the solver, see `audiocraft.solvers.musicgen.MusicGenSolver`, and for the model, | 
					
						
						|  | `audiocraft.models.musicgen.MusicGen`. | 
					
						
						|  | - [AudioGen](https://arxiv.org/abs/2209.15352), a state-of-the-art | 
					
						
						|  | text-to-general-audio generative model. | 
					
						
						|  | - [EnCodec](https://arxiv.org/abs/2210.13438), efficient and high fidelity | 
					
						
						|  | neural audio codec which provides an excellent tokenizer for autoregressive language models. | 
					
						
						|  | See `audiocraft.solvers.compression.CompressionSolver`, and `audiocraft.models.encodec.EncodecModel`. | 
					
						
						|  | - [MultiBandDiffusion](TODO), alternative diffusion-based decoder compatible with EnCodec that | 
					
						
						|  | improves the perceived quality and reduces the artifacts coming from adversarial decoders. | 
					
						
						|  | """ | 
					
						
						|  |  | 
					
						
						|  |  | 
					
						
						|  | from . import data, modules, models | 
					
						
						|  |  | 
					
						
						|  | __version__ = '1.3.0a1' |