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mrq
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vall-e
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db64e6cb59
vall-e
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vall_e
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models
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mrq
b1369e7824
better modality selection (pick AR+NAR by default for the ar+nar model, pick NAR-len by default for the nar-len model), lowered default CFG because it makes the AR+NAR output sped up (but can't be too low since it's required for the NAR-len)
2024-11-19 18:51:17 -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
better modality selection (pick AR+NAR by default for the ar+nar model, pick NAR-len by default for the nar-len model), lowered default CFG because it makes the AR+NAR output sped up (but can't be too low since it's required for the NAR-len)
2024-11-19 18:51:17 -06:00
base.py
I did it.
2024-11-19 12:24:33 -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