An unofficial PyTorch implementation of VALL-E (last updated: 2024.12.11
), utilizing the EnCodec encoder/decoder.
A demo is available on HuggingFace here.
Besides a working PyTorch environment, the only hard requirement is espeak-ng
for phonemizing text:
- Linux users can consult their package managers on installing
espeak
/espeak-ng
. - Windows users are required to install
espeak-ng
.- additionally, you may be required to set the
PHONEMIZER_ESPEAK_LIBRARY
environment variable to specify the path tolibespeak-ng.dll
.
- additionally, you may be required to set the
- In the future, an internal homebrew to replace this would be fantastic.
Simply run pip install git+https://git.ecker.tech/mrq/vall-e
or pip install git+https://github.com/e-c-k-e-r/vall-e
.
This repo is tested under Python versions 3.10.9
, 3.11.3
, and 3.12.3
.
Pre-trained weights can be acquired from
- here or automatically when either inferencing or running the web UI.
./scripts/setup.sh
, a script to setup a proper environment and download the weights. This will also automatically create avenv
.- when inferencing, either through the web UI or CLI, if no model is passed, the default model will download automatically instead, and should automatically update.
The provided documentation under ./docs/ should provide thorough coverage over most, if not all, of this project.
Markdown files should correspond directly to their respective file or folder under ./vall_e/
.