;)

simplified spawning the training process by having it spawn the distributed training processes in the train.py script, so it should work on Windows too

use torchrun instead for multigpu

experimental multi-gpu training (Linux only, because I can't into batch files)

crunchbangs

a bit of UI cleanup, import multiple audio files at once, actually shows progress when importing voices, hides audio metadata / latents if no generated settings are detected, preparing datasets shows its progress, saving a training YAML shows a message when done, training now works within the web UI, training output shows to web UI, provided notebook is cleaned up and uses a venv, etc.