Buckets:

|
download
raw
5.67 kB

AdEMAMix

AdEMAMix is a variant of the Adam optimizer.

bitsandbytes also supports paged optimizers which take advantage of CUDAs unified memory to transfer memory from the GPU to the CPU when GPU memory is exhausted.

AdEMAMix[[api-class]][[bitsandbytes.optim.AdEMAMix]]

bitsandbytes.optim.AdEMAMix[[bitsandbytes.optim.AdEMAMix]]

Source

__init__bitsandbytes.optim.AdEMAMix.__init__https://github.com/bitsandbytes-foundation/bitsandbytes/blob/vr_1972/bitsandbytes/optim/ademamix.py#L108[{"name": "params", "val": ": Iterable"}, {"name": "lr", "val": ": float = 0.001"}, {"name": "betas", "val": ": tuple = (0.9, 0.999, 0.9999)"}, {"name": "alpha", "val": ": float = 5.0"}, {"name": "t_alpha", "val": ": typing.Optional[int] = None"}, {"name": "t_beta3", "val": ": typing.Optional[int] = None"}, {"name": "eps", "val": ": float = 1e-08"}, {"name": "weight_decay", "val": ": float = 0.01"}, {"name": "optim_bits", "val": ": typing.Literal[8, 32] = 32"}, {"name": "min_8bit_size", "val": ": int = 4096"}, {"name": "is_paged", "val": ": bool = False"}]

AdEMAMix8bit[[bitsandbytes.optim.AdEMAMix8bit]]

bitsandbytes.optim.AdEMAMix8bit[[bitsandbytes.optim.AdEMAMix8bit]]

Source

__init__bitsandbytes.optim.AdEMAMix8bit.__init__https://github.com/bitsandbytes-foundation/bitsandbytes/blob/vr_1972/bitsandbytes/optim/ademamix.py#L271[{"name": "params", "val": ": Iterable"}, {"name": "lr", "val": ": float = 0.001"}, {"name": "betas", "val": ": tuple = (0.9, 0.999, 0.9999)"}, {"name": "alpha", "val": ": float = 5.0"}, {"name": "t_alpha", "val": ": typing.Optional[int] = None"}, {"name": "t_beta3", "val": ": typing.Optional[int] = None"}, {"name": "eps", "val": ": float = 1e-08"}, {"name": "weight_decay", "val": ": float = 0.01"}, {"name": "min_8bit_size", "val": ": int = 4096"}, {"name": "is_paged", "val": ": bool = False"}]

AdEMAMix32bit[[bitsandbytes.optim.AdEMAMix32bit]]

bitsandbytes.optim.AdEMAMix32bit[[bitsandbytes.optim.AdEMAMix32bit]]

Source

__init__bitsandbytes.optim.AdEMAMix32bit.__init__https://github.com/bitsandbytes-foundation/bitsandbytes/blob/vr_1972/bitsandbytes/optim/ademamix.py#L356[{"name": "params", "val": ": Iterable"}, {"name": "lr", "val": ": float = 0.001"}, {"name": "betas", "val": ": tuple = (0.9, 0.999, 0.9999)"}, {"name": "alpha", "val": ": float = 5.0"}, {"name": "t_alpha", "val": ": typing.Optional[int] = None"}, {"name": "t_beta3", "val": ": typing.Optional[int] = None"}, {"name": "eps", "val": ": float = 1e-08"}, {"name": "weight_decay", "val": ": float = 0.01"}, {"name": "min_8bit_size", "val": ": int = 4096"}, {"name": "is_paged", "val": ": bool = False"}]

PagedAdEMAMix[[bitsandbytes.optim.PagedAdEMAMix]]

bitsandbytes.optim.PagedAdEMAMix[[bitsandbytes.optim.PagedAdEMAMix]]

Source

__init__bitsandbytes.optim.PagedAdEMAMix.__init__https://github.com/bitsandbytes-foundation/bitsandbytes/blob/vr_1972/bitsandbytes/optim/ademamix.py#L327[{"name": "params", "val": ": Iterable"}, {"name": "lr", "val": ": float = 0.001"}, {"name": "betas", "val": ": tuple = (0.9, 0.999, 0.9999)"}, {"name": "alpha", "val": ": float = 5.0"}, {"name": "t_alpha", "val": ": typing.Optional[int] = None"}, {"name": "t_beta3", "val": ": typing.Optional[int] = None"}, {"name": "eps", "val": ": float = 1e-08"}, {"name": "weight_decay", "val": ": float = 0.01"}, {"name": "optim_bits", "val": ": typing.Literal[8, 32] = 32"}, {"name": "min_8bit_size", "val": ": int = 4096"}]

PagedAdEMAMix8bit[[bitsandbytes.optim.PagedAdEMAMix8bit]]

bitsandbytes.optim.PagedAdEMAMix8bit[[bitsandbytes.optim.PagedAdEMAMix8bit]]

Source

__init__bitsandbytes.optim.PagedAdEMAMix8bit.__init__https://github.com/bitsandbytes-foundation/bitsandbytes/blob/vr_1972/bitsandbytes/optim/ademamix.py#L300[{"name": "params", "val": ": Iterable"}, {"name": "lr", "val": ": float = 0.001"}, {"name": "betas", "val": ": tuple = (0.9, 0.999, 0.9999)"}, {"name": "alpha", "val": ": float = 5.0"}, {"name": "t_alpha", "val": ": typing.Optional[int] = None"}, {"name": "t_beta3", "val": ": typing.Optional[int] = None"}, {"name": "eps", "val": ": float = 1e-08"}, {"name": "weight_decay", "val": ": float = 0.01"}, {"name": "min_8bit_size", "val": ": int = 4096"}]

PagedAdEMAMix32bit[[bitsandbytes.optim.PagedAdEMAMix32bit]]

bitsandbytes.optim.PagedAdEMAMix32bit[[bitsandbytes.optim.PagedAdEMAMix32bit]]

Source

__init__bitsandbytes.optim.PagedAdEMAMix32bit.__init__https://github.com/bitsandbytes-foundation/bitsandbytes/blob/vr_1972/bitsandbytes/optim/ademamix.py#L387[{"name": "params", "val": ": Iterable"}, {"name": "lr", "val": ": float = 0.001"}, {"name": "betas", "val": ": tuple = (0.9, 0.999, 0.9999)"}, {"name": "alpha", "val": ": float = 5.0"}, {"name": "t_alpha", "val": ": typing.Optional[int] = None"}, {"name": "t_beta3", "val": ": typing.Optional[int] = None"}, {"name": "eps", "val": ": float = 1e-08"}, {"name": "weight_decay", "val": ": float = 0.01"}, {"name": "min_8bit_size", "val": ": int = 4096"}]

Xet Storage Details

Size:
5.67 kB
·
Xet hash:
1d53b4e9a300ce58916776c7c6bdb8bcfc64de2ce3251efa2248d75debb452a4

Xet efficiently stores files, intelligently splitting them into unique chunks and accelerating uploads and downloads. More info.