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* example on fine-tuning with LoRA.

* apply make quality.

* fix: pipeline loading.

* Apply suggestions from code review
Co-authored-by: Suraj Patil <surajp815@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* apply suggestions for PR review.
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* apply make style and make quality.

* chore: remove mention of dreambooth from text2image.

* add: weight path and wandb run link.

* Apply suggestions from code review

* apply make style.

* make style
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Switch to huggingface_hub.ModelCard

* Remove modelcards dependency in favor of Jinja2

* Create repo before cloning in examples

* code quality

* improve EMA

* style

* one EMA model

* quality

* fix tests

* fix test

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

* re organise the unconditional script

* backwards compatibility

* default to init values for some args

* fix ort script

* issubclass => isinstance

* update state_dict

* docstr

* doc

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

* use .to if device is passed

* deprecate device

* make flake happy

* fix typo
Co-authored-by: patil-suraj <surajp815@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* [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>

* Support training SD V2 with Flax

Mostly involves supporting a v_prediction scheduler.

The implementation in #1777 doesn't take into account a recent refactor of `scheduling_utils_flax`, so this should be used instead.

* Add to other top-level files.

fix resume step in train_text_to_image example

Fixes to the help for report_to in training scripts.

* misc fixes

* more comments

* Update examples/textual_inversion/textual_inversion.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* set transformers verbosity to warning
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* allow using non-ema weights for training

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

* address more review comment

* reorganise a few lines

* always pad text to max_length to match original training

* ifx collate_fn

* remove unused code

* don't prepare ema_unet, don't register lr scheduler

* style

* assert => ValueError

* add allow_tf32

* set log level

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

* Fix ema decay and clarify nomenclature.

* Rename var.

* 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

* [Flax] Stateless schedulers, fixes and refactors

* Remove scheduling_common_flax and some renames

* Update src/diffusers/schedulers/scheduling_pndm_flax.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Add state checkpointing to other training scripts

* Fix first_epoch

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

* Update Dreambooth checkpoint help message.

* Dreambooth docs: checkpoints, inference from a checkpoint.

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

Remove spurious arg in training scripts.

* do not automatically enable xformers

* uP

* Update requirements.txt

* Update requirements_flax.txt

* Update requirements.txt

* Update requirements_flax.txt

* Update requirements.txt

* Update requirements_flax.txt

* 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>

us from_pretrained to load scheduler

Fixed doc to install from training packages

* 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

* [Examples] Correct path

* uP

load text encoder from subfolder

* [Better scheduler docs] Improve usage examples of schedulers

* finish

* fix warnings and add test

* finish

* more replacements

* adapt fast tests hf token

* correct more

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

* Integrate compatibility with euler
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Update training and fine-tuning docs.

* Update examples README.

* Update README.

* Add Flax fine-tuning section.

* Accept suggestion
Co-authored-by: Anton Lozhkov <anton@huggingface.co>

* Accept suggestion
Co-authored-by: Anton Lozhkov <anton@huggingface.co>
Co-authored-by: Anton Lozhkov <anton@huggingface.co>

fix jnp dtype

* [Flax] Add finetune Stable Diffusion

* temporary fix

* drop_last and seed

* add dtype for mixed precision training

* style

* Add Flax example

remove tensor_format in the new version

* fix ema

* style

* add comment about copy

* style

* quality

* begin text2image script

* loading the datasets, preprocessing & transforms

* handle input features correctly

* add gradient checkpointing support

* fix output names

* run unet in train mode not text encoder

* use no_grad instead of freezing params

* default max steps None

* pad to longest

* don't pad when tokenizing

* fix encode on multi gpu

* fix stupid bug

* add random flip

* add ema

* fix ema

* put ema on cpu

* improve EMA model

* contiguous_format

* don't warp vae and text encode in accelerate

* remove no_grad

* use randn_like

* fix resize

* improve few things

* log epoch loss

* set log level

* don't log each step

* remove max_length from collate

* style

* add report_to option

* make scale_lr false by default

* add grad clipping

* add an option to use 8bit adam

* fix logging in multi-gpu, log every step

* more comments

* remove eval for now

* adress review comments

* add requirements file

* begin readme

* begin readme

* fix typo

* fix push to hub

* populate readme

* update readme

* remove use_auth_token from the script

* address some review comments

* better mixed precision support

* remove redundant to

* create ema model early

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

* better description for train_data_dir

* add diffusers in requirements

* update dataset_name_mapping

* update readme

* add inference example
Co-authored-by: anton-l <anton@huggingface.co>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>