vall-e/vall_e.cpp

vall_e.cpp

This is an implementation that makes use of llama.cpp and encodec.cpp.

At the moment it's very barebones as I try and wrestle with llama.cpp's API without needing to modify its code.

Build

Populate ./include/ with the llama.cpp and encodec.cpp headers.

Populate ./libs/ with the compiled libraries of llama.cpp and encodec.cpp.

Run make.

Required Modifications

encodec.cpp requires updating its GGML copy to the latest version, which requires a few lines to get the CPU backend working.

llama.cpp only possible modification needs to ensure that a non-causal attention mask is used; everything necessary can be hacked together with clever tricks.

To-Do

• converted model to GGUF
  • convert it without modifying any of the existing code, as the tokenizer requires some care
  • actually convert the model properly, as the embeddings differ from the real model
• basic framework
  • load the quantized model
  • orchestrate the required embeddings
  • juggle the output head / classifier properly
• phonemize text
  • with the help of espeak-ng
• tokenize phonemes
  • the tokenizer is being a huge thorn on actual sequences
• load audio from disk
• encode audio
• sum embeddings for the prom and prior resps
• working AR output
  • AR sampling
• working NAR-len output
  • NAR-len sampling
• working NAR output
  • NAR sampling
• decode audio to disk
• a functional CLI
• actually make it work