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mrq
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vall-e
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f284c7ea9c
vall-e
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vall_e
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models
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mrq
7cdfa3dc0c
updated process_datasets.py, added argparsing so I can mostly stop manually editing things, and some other cleanup
2024-08-05 15:59:25 -05:00
..
arch
add adapted MixtralAttention for when I make a bad decision to actually train a MoE
2024-08-04 22:03:22 -05:00
__init__.py
sanity cleanup: moved experimental features under its own thing
2024-06-30 10:37:33 -05:00
ar_nar.py
add adapted MixtralAttention for when I make a bad decision to actually train a MoE
2024-08-04 22:03:22 -05:00
ar.py
fix issue with sft and shared tensors...
2024-08-04 19:56:21 -05:00
base.py
updated process_datasets.py, added argparsing so I can mostly stop manually editing things, and some other cleanup
2024-08-05 15:59:25 -05:00
experimental.py
added what I think is DRY sampling
2024-07-29 19:15:07 -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
changed torch.Tensor().to(device, dtype) to just torch.tensor(..., device, dtype) because it's been bothering my autism that I'm creating tensors then converting rather than creating with the right device/dtype, some 'optimization' to compile the model but it doesnt seem to do anything useful
2024-08-03 22:10:21 -05:00