mrq fc8dfd8617 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
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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	readme tweaks, set the (unused) default model download URL back to the base ar+nar-llama-8 model, as ar+nar-tts+stt-llama-8 was renamed back to it since it performs well	2024-10-05 22:53:53 -05:00
ar_nar.py	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
ar.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
base.py	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
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