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VALL'E
An unofficial PyTorch implementation of VALL-E, utilizing the EnCodec encoder/decoder.
A demo is available on HuggingFace here.
Requirements
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.
Install
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
.
I've tested this repo under Python versions 3.10.9
, 3.11.3
, and 3.12.3
.
Pre-Trained Model
My pre-trained weights can be acquired from here.
A script to setup a proper environment and download the weights can be invoked with ./scripts/setup.sh
. This will automatically create a venv
, and download the ar+nar-llama-8
weights and config file to the right place.
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.
Documentation
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/
.