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[Tracker] modularize inferencing during and after training in the example scripts #6545
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Hey @sayakpaul for text-to-image, SD
haven't gone through the code, will check more if we need to modify it. |
Ideally, this should be delegated to
As done in |
Got it. @sayakpaul I missed that part. Thanks! |
Hey @sayakpaul, @charchit7 |
Hey @sang-k, I have been looking into InstructPix2Pix SD too. Would be happy to collaborate if necessary. |
@coolyashas |
Working on InstructPix2Pix SD |
Has this issue been resolved or are there any pending scripts I could contribute to modularize? cc: @sayakpaul |
Yeah I think this can be closed now :) |
We provide support for running validation inference during and after training in our officially maintained training examples. This is very helpful to keep track of the training progress.
We could modularize some bits in the example to reduce the LoC.
The
train_lcm_distill_lora_sdxl.py
script already does this:diffusers/examples/consistency_distillation/train_lcm_distill_lora_sdxl.py
Line 100 in 33d2b5b
It would be nice to follow something similar for the rest of the scripts too. Here's a handy list of the scripts where we'd like to incorporate this change:
Feel free to comment here if you're interested.
Also, when opening PRs, please target one example at a time and please tag me in the PRs.
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