Since our launch ten months ago, my cofounder and I have continued to improve our music model significantly. You can listen to some cool Staff Picks songs from the latest version here https://sonauto.ai/ , listen to an acapella song I made for my housemate here https://sonauto.ai/song/8a20210c-563e-491b-bb11-f8c6db92ee9b , or try the free and unlimited generations yourself.
However, given there are only two of us right now competing in the "best model and average user UI" race we haven't had the time to build some of the really neat ideas our users and pro musicians have been dreaming up (e..g, DAW plugins, live performance transition generators, etc). The hacker musician community has a rich history of taking new tech and doing really cool and unexpected stuff with it, too.
As such, we're opening up an API that gives full access to the features of our underlying diffusion model (e.g., generation, inpainting, extensions, transition generation, inverse sampling). Here are some things our early test users are already doing with it:
- A cool singing-to-video model by our friends at Lemon Slice: https://x.com/LemonSliceAI/status/1894084856889430147 (try it yourself here https://lemonslice.com/studio)
- Open source wrapper written by one of our musician users: https://github.com/OlaFosheimGrostad/networkmusic
- You can also play with all the API features via our consumer UI here: https://sonauto.ai/create
We also have some examples written in Python here: https://github.com/Sonauto/sonauto-api-examples
- Generate a rock song: https://github.com/Sonauto/sonauto-api-examples/blob/main/ro...
- Download two songs from YouTube (e.g., Smash Mouth to Rick Astley) and generate a transition between them: https://github.com/Sonauto/sonauto-api-examples/blob/main/tr...
- Generate a singing telegram video (powered by ours and also Lemon Slice's API): https://github.com/Sonauto/sonauto-api-examples/blob/main/si...
You can check out the full docs/get your key here: https://sonauto.ai/developers
We'd love to hear what you think, and are open to answering any tech questions about our model too! It's still a latent diffusion model, but much larger and with a much better GAN decoder.