GitLab

update

update

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* Update docs/source/en/quantization/gguf.md
Co-authored-by: Aryan <aryan@huggingface.co>

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Co-authored-by: Aryan <aryan@huggingface.co>

* flux_control_inpaint - failing test_flux_different_prompts

* removing test_flux_different_prompts?

* fix style

* fix from PR comments

* fix style

* reducing guidance_scale in demo

* Update src/diffusers/pipelines/flux/pipeline_flux_control_inpaint.py
Co-authored-by: hlky <hlky@hlky.ac>

* make

* prepare_latents is not copied from

* update docs

* typos

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Co-authored-by: affromero <ubuntu@ip-172-31-17-146.ec2.internal>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: hlky <hlky@hlky.ac>

* Support pass kwargs to sd3 custom attention processor


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

fix: reamde -> readme

* Use `torch` in `get_2d_rotary_pos_embed`

* Add deprecation

fix: licensing header.

* feat: lora support for SANA.

* make fix-copies

* rename test class.

* attention_kwargs -> cross_attention_kwargs.

* Revert "attention_kwargs -> cross_attention_kwargs."

This reverts commit 23433bf9bccc12e0f2f55df26bae58a894e8b43b.

* exhaust 119 max line limit

* sana lora fine-tuning script.

* readme

* add a note about the supported models.

* Apply suggestions from code review
Co-authored-by: Aryan <aryan@huggingface.co>

* style

* docs for attention_kwargs.

* remove lora_scale from pag pipeline.

* copy fix

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Co-authored-by: Aryan <aryan@huggingface.co>

fix: fix typo that cause error

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

update

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* Update src/diffusers/models/transformers/transformer_mochi.py
Co-authored-by: Aryan <aryan@huggingface.co>

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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Aryan <aryan@huggingface.co>

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* Update src/diffusers/quantizers/gguf/utils.py
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* update

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* Update docs/source/en/quantization/gguf.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* update

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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

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

* add lora support for ltx

* add tests

* fix copied from comments

* update

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

update

add contribution note for lawrence.

* attnprocessors

* lora

* make style

* fix

* fix

* sana

* typo

* torchao quantizer


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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

Fix repaint scheduler

* Use non-human subject in StableDiffusion3ControlNetPipeline example

* make style

use_flow_sigmas copy

* Add `dynamic_shifting` to SD3

* calculate_shift

* FlowMatchHeunDiscreteScheduler doesn't support mu

* Inpaint/img2img

add rest of the lora loader mixins to the docs.

* Update pipeline_controlnet.py

* make style

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Co-authored-by: hlky <hlky@hlky.ac>

* copy transformer

* copy vae

* copy pipeline

* make fix-copies

* refactor; make original code work with diffusers; test latents for comparison generated with this commit

* move rope into pipeline; remove flash attention; refactor

* begin conversion script

* make style

* refactor attention

* refactor

* refactor final layer

* their mlp -> our feedforward

* make style

* add docs

* refactor layer names

* refactor modulation

* cleanup

* refactor norms

* refactor activations

* refactor single blocks attention

* refactor attention processor

* make style

* cleanup a bit

* refactor double transformer block attention

* update mochi attn proc

* use diffusers attention implementation in all modules; checkpoint for all values matching original

* remove helper functions in vae

* refactor upsample

* refactor causal conv

* refactor resnet

* refactor

* refactor

* refactor

* grad checkpointing

* autoencoder test

* fix scaling factor

* refactor clip

* refactor llama text encoding

* add coauthor
Co-Authored-By: "Gregory D. Hunkins" <greg@ollano.com>

* refactor rope; diff: 0.14990234375; reason and fix: create rope grid on cpu and move to device

Note: The following line diverges from original behaviour. We create the grid on the device, whereas
original implementation creates it on CPU and then moves it to device. This results in numerical
differences in layerwise debugging outputs, but visually it is the same.

* use diffusers timesteps embedding; diff: 0.10205078125

* rename

* convert

* update

* add tests for transformer

* add pipeline tests; text encoder 2 is not optional

* fix attention implementation for torch

* add example

* update docs

* update docs

* apply suggestions from review

* refactor vae

* update

* Apply suggestions from code review
Co-authored-by: hlky <hlky@hlky.ac>

* Update src/diffusers/pipelines/hunyuan_video/pipeline_hunyuan_video.py
Co-authored-by: hlky <hlky@hlky.ac>

* Update src/diffusers/pipelines/hunyuan_video/pipeline_hunyuan_video.py
Co-authored-by: hlky <hlky@hlky.ac>

* make fix-copies

* update

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Co-authored-by: "Gregory D. Hunkins" <greg@ollano.com>
Co-authored-by: hlky <hlky@hlky.ac>

update

minor stuff to ltx video docs.

update always test pipelines list.