huggingface
fix min-snr implementation
What does this PR do?
Fixes the implementation of min-snr training for v-prediction models
Based on implementation seen here. https://github.com/kohya-ss/sd-scripts/blob/main/library/custom_train_functions.py#L66
These two graphs show the weight scheme based on timestep from the kohya implementation.
the current implementation in diffusers takes the eps weight and increases everything by + 1, it appears that the +1 should be relocated to the denominator
- Schedulers: @yiyixuxu
- Training examples: @sayakpaul
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@ethansmith2000
would you be able to make style? will merge once CI is green and we will ask the community to apply the same change
This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.
Please note that issues that do not follow the contributing guidelines are likely to be ignored.