Buckets:

|
download
raw
6.49 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]]

bitsandbytes.optim.AdEMAMix(params: Iterable, lr: float = 0.001, betas: tuple = (0.9, 0.999, 0.9999), alpha: float = 5.0, t_alpha: typing.Optional[int] = None, t_beta3: typing.Optional[int] = None, eps: float = 1e-08, weight_decay: float = 0.01, optim_bits: typing.Literal[8, 32] = 32, min_8bit_size: int = 4096, is_paged: bool = False)

Source

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

__init__(params: Iterable, lr: float = 0.001, betas: tuple = (0.9, 0.999, 0.9999), alpha: float = 5.0, t_alpha: typing.Optional[int] = None, t_beta3: typing.Optional[int] = None, eps: float = 1e-08, weight_decay: float = 0.01, optim_bits: typing.Literal[8, 32] = 32, min_8bit_size: int = 4096, is_paged: bool = False)

Source

AdEMAMix8bit[[bitsandbytes.optim.AdEMAMix8bit]]

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

bitsandbytes.optim.AdEMAMix8bit(params: Iterable, lr: float = 0.001, betas: tuple = (0.9, 0.999, 0.9999), alpha: float = 5.0, t_alpha: typing.Optional[int] = None, t_beta3: typing.Optional[int] = None, eps: float = 1e-08, weight_decay: float = 0.01, min_8bit_size: int = 4096, is_paged: bool = False)

Source

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

__init__(params: Iterable, lr: float = 0.001, betas: tuple = (0.9, 0.999, 0.9999), alpha: float = 5.0, t_alpha: typing.Optional[int] = None, t_beta3: typing.Optional[int] = None, eps: float = 1e-08, weight_decay: float = 0.01, min_8bit_size: int = 4096, is_paged: bool = False)

Source

AdEMAMix32bit[[bitsandbytes.optim.AdEMAMix32bit]]

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

bitsandbytes.optim.AdEMAMix32bit(params: Iterable, lr: float = 0.001, betas: tuple = (0.9, 0.999, 0.9999), alpha: float = 5.0, t_alpha: typing.Optional[int] = None, t_beta3: typing.Optional[int] = None, eps: float = 1e-08, weight_decay: float = 0.01, min_8bit_size: int = 4096, is_paged: bool = False)

Source

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

__init__(params: Iterable, lr: float = 0.001, betas: tuple = (0.9, 0.999, 0.9999), alpha: float = 5.0, t_alpha: typing.Optional[int] = None, t_beta3: typing.Optional[int] = None, eps: float = 1e-08, weight_decay: float = 0.01, min_8bit_size: int = 4096, is_paged: bool = False)

Source

PagedAdEMAMix[[bitsandbytes.optim.PagedAdEMAMix]]

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

bitsandbytes.optim.PagedAdEMAMix(params: Iterable, lr: float = 0.001, betas: tuple = (0.9, 0.999, 0.9999), alpha: float = 5.0, t_alpha: typing.Optional[int] = None, t_beta3: typing.Optional[int] = None, eps: float = 1e-08, weight_decay: float = 0.01, optim_bits: typing.Literal[8, 32] = 32, min_8bit_size: int = 4096)

Source

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

__init__(params: Iterable, lr: float = 0.001, betas: tuple = (0.9, 0.999, 0.9999), alpha: float = 5.0, t_alpha: typing.Optional[int] = None, t_beta3: typing.Optional[int] = None, eps: float = 1e-08, weight_decay: float = 0.01, optim_bits: typing.Literal[8, 32] = 32, min_8bit_size: int = 4096)

Source

PagedAdEMAMix8bit[[bitsandbytes.optim.PagedAdEMAMix8bit]]

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

bitsandbytes.optim.PagedAdEMAMix8bit(params: Iterable, lr: float = 0.001, betas: tuple = (0.9, 0.999, 0.9999), alpha: float = 5.0, t_alpha: typing.Optional[int] = None, t_beta3: typing.Optional[int] = None, eps: float = 1e-08, weight_decay: float = 0.01, min_8bit_size: int = 4096)

Source

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

__init__(params: Iterable, lr: float = 0.001, betas: tuple = (0.9, 0.999, 0.9999), alpha: float = 5.0, t_alpha: typing.Optional[int] = None, t_beta3: typing.Optional[int] = None, eps: float = 1e-08, weight_decay: float = 0.01, min_8bit_size: int = 4096)

Source

PagedAdEMAMix32bit[[bitsandbytes.optim.PagedAdEMAMix32bit]]

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

bitsandbytes.optim.PagedAdEMAMix32bit(params: Iterable, lr: float = 0.001, betas: tuple = (0.9, 0.999, 0.9999), alpha: float = 5.0, t_alpha: typing.Optional[int] = None, t_beta3: typing.Optional[int] = None, eps: float = 1e-08, weight_decay: float = 0.01, min_8bit_size: int = 4096)

Source

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

__init__(params: Iterable, lr: float = 0.001, betas: tuple = (0.9, 0.999, 0.9999), alpha: float = 5.0, t_alpha: typing.Optional[int] = None, t_beta3: typing.Optional[int] = None, eps: float = 1e-08, weight_decay: float = 0.01, min_8bit_size: int = 4096)

Source

Xet Storage Details

Size:
6.49 kB
·
Xet hash:
407d6247ea2dc63f3f60989cf374e837ce663fb6766643b5f0ea7c1f21a8bae4

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