|
|
|
|
|
|
|
|
|
|
|
""" |
|
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__ = '1.0.0' |
|
|