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It appears that LMDeploy does not support native BF16 inference, but instead converts it to FP16.
But this may lead to precision overflow (#385), is there a plan to support BF16 inference?
No response
The text was updated successfully, but these errors were encountered:
Yes, we will bring back BF16 support after a few major refactoring to lower the maintainance cost.
BTW, which model are you testing has overflow issue using f16 type?
Sorry, something went wrong.
Thank you! Look forward to the follow-up progress.
And we encountered this problem with an internal inference framework and internal models. These models are trained with BF16 precision.
I see.
Have you checked in which layer or operator the overflow arises?
Sorry, I didn't check it carefully.
But when I changed the precision to BF16, I can get the correct result.
PR #803
lzhangzz
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Motivation
It appears that LMDeploy does not support native BF16 inference, but instead converts it to FP16.
But this may lead to precision overflow (#385), is there a plan to support BF16 inference?
Related resources
No response
Additional context
No response
The text was updated successfully, but these errors were encountered: