GitLab

* 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>

* add community pipeline: StableUnCLIPPipeline

* reformt stable_unclip.py with isort and black

* Switch to huggingface_hub.ModelCard

* Remove modelcards dependency in favor of Jinja2

* Create repo before cloning in examples

* code quality

Fix

* 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] up lora training

* finish

* finish

* finish model card

* [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>

no more autocast

fix lr scheduler

fix typos

* [Community] Fix merger

* finish

Fix a couple typos in Dreambooth readme.

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

* Example tests

* fix

* implemented multi subject dreambooth in research_projects

* minor edits to readme

* added style and quality fixes
Co-authored-by: Krista Opsahl-Ong <kristaopsahlong@gmail.com>

Update README.md

TypeError: Size should be int or sequence. Got <class 'dict'>

changed named arg to self.tokenizer from `truncaton` to `truncation` according to Tokenizer docs (https://huggingface.co/docs/tokenizers/api/tokenizer#tokenizers.Tokenizer.truncation)

* [dreambooth] low precision guard

* fix

* add docs to cli args

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

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

Support ColossalAi for Dreamblooth

* added first version of the tiled upscaling pipeline

* reformatted to pass code quality tests

* Various Fixes for Flax Dreambooth

- Correctly update the progress bar every epoch
- Allow specifying a pretrained VAE
- Allow specifying a revision to pretrained models
- Cache compiled models between invocations (speeds up TPU execution a lot!)
- Save intermediate checkpoints by specifying `save_steps`

* Don't die when save_steps is not set.

* Address CR

* Address comments

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

Fix default lr-scaling cli argument

* 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

* [Deterministic torch randn] Allow tensors to be generated on CPU

* fix more

* up

* fix more

* up

* Update src/diffusers/utils/torch_utils.py
Co-authored-by: Anton Lozhkov <anton@huggingface.co>

* Apply suggestions from code review

* up

* up

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

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>

Fix typo in train_dreambooth_inpaint.

* 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>

update loss computation

* Fix ema decay and clarify nomenclature.

* Rename var.

* move files a bit

* more refactors

* fix more

* more fixes

* fix more onnx

* make style

* upload

* fix

* up

* fix more

* up again

* up

* small fix

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

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

Co-authored-by: Henrik Forstén <henrik.forsten@gmail.com>

* update TI script

* make flake happy

* fix typo

* initial

* type hints

* update scheduler type hint

* add to README

* add example generation to README

* v -> mix_factor

* load scheduler from pretrained