GitLab

* Updated lora inference instructions

* Update examples/dreambooth/README.md
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Update README.md

* Update README.md

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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* adapt example scripts to use PEFT

* Update examples/text_to_image/train_text_to_image_lora.py

* fix

* add for SDXL

* oops

* make sure to install peft

* fix

* fix

* fix dreambooth and lora

* more fixes

* add peft to requirements.txt

* fix

* final fix

* add peft version in requirements

* remove comment

* change variable names

* add few lines in readme

* add to reqs

* style

* fix issues

* fix lora dreambooth xl tests

* init_lora_weights to gaussian and add out proj where missing

* ammend requirements.

* ammend requirements.txt

* add correct peft versions

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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* dreambooth training

* train_dreambooth validation scheduler

* set a particular scheduler via a string

* modify readme after setting a particular scheduler via a string

* modify readme after setting a particular scheduler

* use importlib to set a particular scheduler

* import with correct sort

fix: Typo in dreambooth example README.md

* add dreambooth lora script for SDXL incorporating latest changes.

* remove use_auth_token=True.

* add: documentation

* remove unneeded cli.

* increase the number of training steps in the readme.

* add LoraLoaderMixin to the subclassing mix.

* add sdxl lora dreambooth test.

* add: inference code sample.

* add: refiner output.

* add LoraLoaderMixin to the mix of classes of StableDiffusionXLImg2ImgPipeline.

* change default resolution of DreamBoothDataset.

* better sdxl report path.

* Apply suggestions from code review
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

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Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* dreambooth if docs - stage II, more info

* Update docs/source/en/training/dreambooth.mdx
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update docs/source/en/training/dreambooth.mdx
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update docs/source/en/training/dreambooth.mdx
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* download instructions for downsized images

* update source README to match docs

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Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* dreambooth docs torch.compile note

* Update examples/dreambooth/README.md
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Update examples/dreambooth/README.md
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* fix: scale_lr and sync example readme and docs.

* fix doc link.

* Update Dreambooth README

* Adapt all docs as well

* automatically write model card

* fix

* make style

* 👽

 qol improvements for LoRA.

* better function name?

* fix: LoRA weight loading with the new format.

* address Patrick's comments.

* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* change wording around encouraging the use of load_lora_weights().

* fix: function name.

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

* add: LoRA text encoder support for DreamBooth example.

* fix initialization.

* fix: modification call.

* add: entry in the readme.

* use dog dataset from hub.

* fix: params to clip.

* add entry to the LoRA doc.

* add: tests for lora.

* remove unnecessary list comprehension./

* Dreambooth: use `optimizer.zero_grad(set_to_none=True)` to reduce VRAM usage

* Allow the user to control `optimizer.zero_grad(set_to_none=True)` with --set_grads_to_none

* Update Dreambooth readme

* Fix link in readme

* Fix header size in readme

Fix

* [Lora] first upload

* add first lora version

* upload

* more

* first training

* up

* correct

* improve

* finish loaders and inference

* up

* up

* fix more

* up

* finish more

* finish more

* up

* up

* change year

* revert year change

* Change lines

* Add cloneofsimo as co-author.
Co-authored-by: Simo Ryu <cloneofsimo@gmail.com>

* finish

* fix docs

* Apply suggestions from code review
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* upload

* finish
Co-authored-by: Simo Ryu <cloneofsimo@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Suraj Patil <surajp815@gmail.com>

Fix a couple typos in Dreambooth readme.

* Update README.md
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Make xformers optional even if it is available

* Raise exception if xformers is used but not available

* Rename use_xformers to enable_xformers_memory_efficient_attention

* Add a note about xformers in README

* Reformat code style

* Section header for in-painting, inference from checkpoint.

* Inference: link to section to perform inference from checkpoint.

* Move Dreambooth in-painting instructions to the proper place.

* add check_min_version for examples

* move __version__ to the top

* Apply suggestions from code review
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* fix comment

* fix error_message

* adapt the install message
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Research folder

* Update examples/research_projects/README.md

* up

* Create train_dreambooth_inpaint.py

train_dreambooth.py adapted to work with the inpaint model, generating random masks during the training

* Update train_dreambooth_inpaint.py

refactored train_dreambooth_inpaint with black

* Update train_dreambooth_inpaint.py

* Update train_dreambooth_inpaint.py

* Update train_dreambooth_inpaint.py

Fix prior preservation

* add instructions to readme, fix SD2 compatibility

* [Dreambooth] Make compatible with alt diffusion

* make style

* add example

* add get_velocity

* add v prediction for training

* fix saving

* add revision arg

* fix saving

* save checkpoints dreambooth

* fix saving embeds

* add instruction in readme

* quality

* noise_pred -> model_pred

* use accelerator to check mixed_precision

* default `mixed_precision` to `None`

* pass mixed_precision to accelerate launch

* add 'conda install cudatoolkit' to dreambooth 'training on 16GB' example 

fixes https://github.com/huggingface/diffusers/issues/1207



* Apply suggestions from code review
Co-authored-by: Suraj Patil <surajp815@gmail.com>

Update README.md

fixed typo

* [Flax] Add DreamBooth

* fix sample rng

* style

* not reuse rng

* add dtype for mixed precision training

* Add Flax example

dont' use safety check when generating prior images

Add --sample_batch_size=1 to the 8 GB dreambooth script

* allow fine-tuning text encoder

* fix a few things

* update readme

* Support deepspeed

* Dreambooth DeepSpeed documentation

* Remove unnecessary casts, documentation

Due to recent commits some casts to half precision are not necessary
anymore.

Mention that DeepSpeed's version of Adam is about 2x faster.

* Review comments