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Add Community Example Consistency Training Script #6717

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merged 10 commits into from
Jan 26, 2024

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dg845
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@dg845 dg845 commented Jan 26, 2024

What does this PR do?

This PR adds a script which implements consistency training (CT), an algorithm which trains consistency models (CMs) from scratch, which was introduced in Consistency Models and refined in Improved Techniques for Training Consistency Models. The script supports both unconditional and class-conditional training.

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Who can review?

Anyone in the community is free to review the PR once the tests have passed. Feel free to tag
members/contributors who may be interested in your PR.

@patrickvonplaten
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Could you add to the research_projects folder instead? We keep the experimental training scripts there. @patil-suraj could you give this a look?

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The docs for this PR live here. All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.

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dg845 commented Jan 26, 2024

The script has been moved from examples/community/ to examples/research_projects/consistency_training/.

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Awesome - great effort @dg845!

@patrickvonplaten patrickvonplaten merged commit b4220e9 into huggingface:main Jan 26, 2024
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@dg845 dg845 deleted the consistency-training-script branch January 30, 2024 02:48
AmericanPresidentJimmyCarter pushed a commit to AmericanPresidentJimmyCarter/diffusers that referenced this pull request Apr 26, 2024
* initial commit for unconditional/class-conditional consistency training script

* make style

* Add entry for consistency training script in community README.

* Move consistency training script from community to research_projects/consistency_training

* Add requirements.txt and README to research_projects/consistency_training directory.

* Manually revert community README changes for consistency training.

* Fix path to script after moving script to research projects.

* Add option to load U-Net weights from pretrained model.

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Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
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4 participants