mrq ccf71dc1b6 added option to load from a model state dict directly instead of a yaml (to-do: do this for LoRAs too), automatically download the default model if none is provided		2024-10-25 22:15:15 -05:00
..
arch	made greedy AR sampling viable (and preferable), with caveats (per comment in vall_e.models.ar_nar)	2024-10-18 16:55:00 -05:00
__init__.py	added option to load from a model state dict directly instead of a yaml (to-do: do this for LoRAs too), automatically download the default model if none is provided	2024-10-25 22:15:15 -05:00
ar_nar.py	adjusted how i want to pass eval kwargs	2024-10-25 20:38:09 -05:00
ar.py	added prefixing with silence (was to test something, currently hidden under cfg.experimental=True)	2024-10-18 17:19:52 -05:00
base.py	modified default arguments (ar temp = 0 and rep pen = 1.125 seems to be stable, at least given the few things i tested), do not pass top k/top p/min p to NAR even though technically none of those things should matter when greedy sampling	2024-10-22 18:12:39 -05:00
experimental.py	moved prints to use logger, edited readme (fused_attn doesnt seem stable for training)	2024-08-29 13:27:16 -05:00
lora.py	naive model offloading support (handles automatically splitting parts of the model to requested device per memory constraints, either inferred or requested in the yaml, input tensors are automatically migrated to the right device, it SEEMS to work for training under the test trainer when split between GPU and CPU) (this was specifically only because that Flux imagegen model released so I can test it there)	2024-08-01 20:12:06 -05:00
nar.py	cleaned up unused config flags, allow less strict yaml by pruning missing keys, renamed some dataset configs to be more unified	2024-10-17 17:06:48 -05:00