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standardize model card template t2i-sdxl

standardize model card t2i-lora

* standardize model card

* fix base_model

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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: YiYi Xu <yixu310@gmail.com>
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* fix

* add tests

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Co-authored-by: yiyixuxu <yixu310@gmail,com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

add
Co-authored-by: yiyixuxu <yixu310@gmail,com>

* post release

* style

* Empty-Commit

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

* deprecate certain lora methods from the old backend.

* uncomment necessary things.

* safe remove old lora backend 👋

[FIX] IMPORTANT: rgb normalization

update

* controlnet

* style

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

* refactor decode latents in video pipelines

* make fix-copies

controlnet-sdxl

* controlnet-flax

* style

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

* Fix Compatibility Issues in stable_diffusion_xl_reference.py

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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: YiYi Xu <yixu310@gmail.com>

Co-authored-by: wangshaoxiao <wangshaoxiao@xiaomi.com>

* Add vae tiling in img2img and inpaint

* Add vae tiling not slicing

Remove <cat-toy> validation prompt from examples/textual_inversion/textual_inversion_sdxl.py (#6877)

Remove <cat-toy> validation prompt from textual_inversion_sdxl.py

The `<cat-toy>` validation prompt is a default choice for the example task in the README. But no other part of `textual_inversion_sdxl.py` references the cat toy and `textual_inversion.py` has a default validation prompt of `None` as well.

So bring `textual_inversion_sdxl.py` in line with `textual_inversion.py` and change default validation prompt to `None`

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

change to 2024

Co-authored-by: Patryk Bartkowiak <patryk.bartkowiak@tcl.com>
Co-authored-by: Linoy Tsaban <57615435+linoytsaban@users.noreply.github.com>

This fixes #6899.

* attention_head_dim

* debug

* print more info

* correct num_attention_heads behaviour

* down_block_num_attention_heads -> num_attention_heads.

* correct the image link in doc.

* add: deprecation for num_attention_head

* fix: test argument to use attention_head_dim

* more fixes.

* quality

* address comments.

* remove depcrecation.

* add: support for passing ip adapter image embeddings

* debugging

* make feature_extractor unloading conditioned on safety_checker

* better condition

* type annotation

* index to look into value slices

* more debugging

* debugging

* serialize embeddings dict

* better conditioning

* remove unnecessary prints.

* Update src/diffusers/loaders/ip_adapter.py
Co-authored-by: YiYi Xu <yixu310@gmail.com>

* make fix-copies and styling.

* styling and further copy fixing.

* fix: check_inputs call in controlnet sdxl img2img pipeline

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Co-authored-by: YiYi Xu <yixu310@gmail.com>

* Fix: training resume from fp16 for lcm distill lora sdxl

* Fix coding quality - run linter

* Fix 1 - shift mixed precision cast before optimizer

* Fix 2 - State dict errors by removing load_lora_into_unet

* Update train_lcm_distill_lora_sdxl.py - Revert default cache dir to None

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

* remove torch_dtype from to()

* remove torch_dtype from usage scripts.

* remove old lora backend

* Revert "remove old lora backend"

This reverts commit adcddf6ba421f847e7da2a0ce57b9456cae43356.

[ip-adapter] make sure length of `scale` is same as number of ip-adapters when using  `set_ip_adapter_scale` (#6884)

add
Co-authored-by: yiyixuxu <yixu310@gmail,com>

* feat: standarize model card creation for dreambooth training.

* correct 'inference

* remove comments.

* take component out of kwargs

* style

* add: card template to have a leaner description.

* widget support.

* propagate changes to train_dreambooth_lora

* propagate changes to custom diffusion

* make widget properly type-annotated

* fix: callback function name is incorrect

On this tutorial there is a function defined and then used inside `callback_on_step_end` argument, but the name was not correct (mismatch)

* fix: typo in num_timestep (correct is num_timesteps)

fixed property name

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* update

* update

* update

This reverts commit 15f6b224.

* remove _to_tensor

* remove _to_tensor definition

* remove _collapse_frames_into_batch

* remove lora for not bloating the code.

* remove sample_size.

* simplify code a bit more

* ensure timesteps are always in tensor.

* Fix `AutoencoderTiny` with `use_slicing`

When using slicing with AutoencoderTiny, the encoder mistakenly encodes the entire batch for every image in the batch.

* Fixed formatting issue

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