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Merge branch 'main' of https://github.com/borisdayma/dalle-mini into main
0a691de
feat: log num_parameters early
7cfe576
fix: distributed shampoo class
696422e
feat: update distributed_shampoo
5996680
feat(modeling): simplify abstract_init
fa72aa7
feat(train) - handle multiple nodes (#130)
0952927
unverified
feat: handle model parallel
1bb3269
feat(train): more custom x-axis
5f28cd2
feat(train): split artifact into model/state (#128)
7c4c287
unverified
fix: style
386f839
fix(train): opt_state_shape for distributed_shampoo
225b6ff
feat(train): split artifact into model/state
fa5b058
style(tokenizer): remove unused variables
605df32
feat: use fast tokenizer
767d78a
feat(train): another 25% faster
14abe8c
Merge pull request #127 from borisdayma/pjit-t5x
e4401dd
unverified
feat(train): overhead from 70% to 1% 🥳
2b7f5f1
feat(pjit): follow t5x style
7b5868f
fix(train): grads spec
00710bc
feat(train): improve pjit speed
f254058
fix(train): consider correct batch size
b7c7458
feat(train): custom start_preconditioning_step
8149924
feat(train): handle distributed_shampoo in pjit
032f623
feat: update distributed_shampoo + fix None spec
8a9e367
feat(train): distributed_shampoo with pjit
cc34d07
feat(train): use pjit (#125)
f5239e1
unverified
style: unsused import
7a176b9
fix style
f044cb8
feat(train): restore opt_state efficiently
1bfc1b5
feat(model): clean way to load on cpu
12f323d
feat(train): load model on CPU
3d43591
feat(train): different rng per node
2d212d8
feat(train): no batch dimension with pjit
df1fe19
feat(train): progress on pjit
49597a2
feat(train): start pjit support
0081723
feat: use_artifact if run existing
a5ed112
Load from wandb artifact (#121)
f69b21b
unverified
Style (isort).
f9d51f7
Pedro Cuenca
commited on
feat(train): update sweep config
bbbf7c8
Use DalleBartTokenizer. State restoration reverted to previous method:
ae983d7
Pedro Cuenca
commited on
Tokenizer, config, model can be loaded from wandb.
7e48337
Pedro Cuenca
commited on