mrq b2907ae7e0 seems that my PromEmbedding/RespEmbedding doesn't actually work all that well, naively using dedicated MultiEmbeddings for AR/NAR in the monolithic model is the best way to go		2023-09-08 01:03:24 -05:00
..
emb	(need to verify) added modifying model size and config bool to align with VALL-E continuous' methodology	2023-09-01 17:19:34 -05:00
engines	added option to specify parameters to freeze per-model in YAML (because I need to see about committing atrocities with convering an AR into an AR+NAR)	2023-09-07 18:19:51 -05:00
models	seems that my PromEmbedding/RespEmbedding doesn't actually work all that well, naively using dedicated MultiEmbeddings for AR/NAR in the monolithic model is the best way to go	2023-09-08 01:03:24 -05:00
utils	also cull frozen_params in the params optimizer receives to reduce VRAM it consumes	2023-09-07 18:27:02 -05:00
__init__.py
__main__.py
config.py	added option to specify parameters to freeze per-model in YAML (because I need to see about committing atrocities with convering an AR into an AR+NAR)	2023-09-07 18:19:51 -05:00
data.py	added per-speaker samplers	2023-09-03 21:27:13 -05:00
export.py
inference.py	seems that my PromEmbedding/RespEmbedding doesn't actually work all that well, naively using dedicated MultiEmbeddings for AR/NAR in the monolithic model is the best way to go	2023-09-08 01:03:24 -05:00
plot.py	integrated plot script, added tts-c task token to help the model be able to mix between normal VALL-E and VALL-E continuous	2023-09-02 16:29:53 -05:00
train.py	seems that my PromEmbedding/RespEmbedding doesn't actually work all that well, naively using dedicated MultiEmbeddings for AR/NAR in the monolithic model is the best way to go	2023-09-08 01:03:24 -05:00