My guess: 1. `codec`: First, compress 16k samplerate audio into 8 samples per second with convolutions. Then, vector quantize to 128 bits (probably 8 floats) t

My guess: 1. `codec`: First, compress 16k samplerate audio into 8 samples per second with convolutions. Then, vector quantize to 128 bits (probably 8 floats) to get a codec. This is not nearly enough bits to actually represent the audio, it's more to represent phenomes. 2. `vae` -> This looks like a VAE-based diffusion model, that uses the codec as its prompt. 3. `dev` -> This is a next-codec prediction model. Put together, it probably runs like so: 1. Turn your prompt into tokens with the `codec`. 2. If you want s more seconds of audio, use `dev` to predict 8 * s more tokens. 3. Turn it back into audio with the `vae` diffusion model.