mrq be83ddabaa better causal-ness for split loss calc, and also do masking for NAR-len for it		2024-11-13 10:17:52 -06:00
..
arch	This better work	2024-11-09 18:04:59 -06:00
__init__.py	unified nar.py into ar_nar.py	2024-11-10 12:19:48 -06:00
ar_nar.py	do not pass timestep token/embedding since it doesn't seem to matter at all after all, fixed training masking rate to 80% because a paper said so	2024-11-13 09:07:10 -06:00
base.py	better causal-ness for split loss calc, and also do masking for NAR-len for it	2024-11-13 10:17:52 -06:00
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