mrq 4a71981456 normalize sampler index by batch size (if not using batched sampler), add option to cap out utterances for a speaker, some other things		2024-11-18 12:46:50 -06:00
..
emb	fixes	2024-11-10 20:37:50 -06:00
engines	ugh	2024-11-14 07:34:22 -06:00
ext	maybe final tweaks, I really needed to unify my json read/write and orjson is proven to be fast enough for me to try and rely on it more	2024-09-17 22:57:04 -05:00
models	swap priority to use nar-len if available, added notes	2024-11-18 09:40:04 -06:00
utils	default set cfg strength to 3.0 since the reference model is updated	2024-11-17 10:23:40 -06:00
__init__.py	Rewrite init	2023-08-02 21:53:35 +00:00
__main__.py	new meme sampler PogChamp new meme sampler PogChamp (it sort of helps?)	2024-11-12 22:30:09 -06:00
config.py	normalize sampler index by batch size (if not using batched sampler), add option to cap out utterances for a speaker, some other things	2024-11-18 12:46:50 -06:00
data.py	normalize sampler index by batch size (if not using batched sampler), add option to cap out utterances for a speaker, some other things	2024-11-18 12:46:50 -06:00
demo.py	set option to set training masking ratio (I don't think for tts a fixed masking ratio is beneficial since the magic of the AR+NAR is being able to still reference the prior sequence of tokens for predicting things)	2024-11-17 17:04:07 -06:00
export.py	tweaks and fixes for lora stuffs	2024-09-08 18:05:21 -05:00
inference.py	swap priority to use nar-len if available, added notes	2024-11-18 09:40:04 -06:00
plot.py	very, very naive layerskip speculative sampling (it just checks if the current layer's state is good enough)	2024-11-02 11:49:05 -05:00
samplers.py	new meme sampler PogChamp new meme sampler PogChamp (it sort of helps?)	2024-11-12 22:30:09 -06:00
train.py	default set cfg strength to 3.0 since the reference model is updated	2024-11-17 10:23:40 -06:00
webui.py	default set cfg strength to 3.0 since the reference model is updated	2024-11-17 10:23:40 -06:00