You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Hi thanks for the library! It would be great if the optimizers can be run on CPU. For example, I would like to try adamw_8bit to full-finetune a 8B model on a 24GB GPU card (RTX4090). With deepspeed offload, the GPU memory is OK, but the CPU memory requirement is still very huge, partially because it uses normal adamw, thus needs 8x8=64GB for the optimizer itself.
This package creates the super helpful adamw_8bit, thus I would appreciate it if it can be used with the settings above, hopefully reducing 64GB to 8x2=16GB for optimizer state.
Motivation
(see above)
Your contribution
Yes
The text was updated successfully, but these errors were encountered:
See #1021. I proposed that this should be a step on the path of implementing cross platform support (especially Apple Silicon, as CUDA and Apple Silicon won't run on the same hardware, which makes validation complicated)
Feature request
Hi thanks for the library! It would be great if the optimizers can be run on CPU. For example, I would like to try adamw_8bit to full-finetune a 8B model on a 24GB GPU card (RTX4090). With deepspeed offload, the GPU memory is OK, but the CPU memory requirement is still very huge, partially because it uses normal adamw, thus needs 8x8=64GB for the optimizer itself.
This package creates the super helpful adamw_8bit, thus I would appreciate it if it can be used with the settings above, hopefully reducing 64GB to 8x2=16GB for optimizer state.
Motivation
(see above)
Your contribution
Yes
The text was updated successfully, but these errors were encountered: